Merge branch 'ggerganov:master' into master

pull/222/head
katsu560 3 years ago committed by GitHub
commit c1808cd641
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2
.gitignore vendored

@ -13,10 +13,12 @@ build-sanitize-thread/
main
stream
command
bench
sync.sh
compile_commands.json
examples/arm_neon.h
examples/whisper.objc/whisper.objc.xcodeproj/xcshareddata
examples/whisper.objc/whisper.objc.xcodeproj/xcuserdata/
examples/whisper.objc/whisper.objc.xcodeproj/project.xcworkspace/xcuserdata

@ -134,7 +134,7 @@ libwhisper.so: ggml.o whisper.o
$(CXX) $(CXXFLAGS) -shared -o libwhisper.so ggml.o whisper.o $(LDFLAGS)
clean:
rm -f *.o main stream bench libwhisper.a libwhisper.so
rm -f *.o main stream command bench libwhisper.a libwhisper.so
#
# Examples
@ -149,6 +149,9 @@ main: examples/main/main.cpp ggml.o whisper.o
stream: examples/stream/stream.cpp ggml.o whisper.o
$(CXX) $(CXXFLAGS) examples/stream/stream.cpp ggml.o whisper.o -o stream $(CC_SDL) $(LDFLAGS)
command: examples/command/command.cpp ggml.o whisper.o
$(CXX) $(CXXFLAGS) examples/command/command.cpp ggml.o whisper.o -o command $(CC_SDL) $(LDFLAGS)
bench: examples/bench/bench.cpp ggml.o whisper.o
$(CXX) $(CXXFLAGS) examples/bench/bench.cpp ggml.o whisper.o -o bench $(LDFLAGS)
@ -198,7 +201,7 @@ tiny.en tiny base.en base small.en small medium.en medium large: main
@echo ""
@for f in samples/*.wav; do \
echo "----------------------------------------------" ; \
echo "[+] Running base.en on $$f ... (run 'ffplay $$f' to listen)" ; \
echo "[+] Running $@ on $$f ... (run 'ffplay $$f' to listen)" ; \
echo "----------------------------------------------" ; \
echo "" ; \
./main -m models/ggml-$@.bin -f $$f ; \

@ -36,9 +36,11 @@ As an example, here is a video of running the model on an iPhone 13 device - ful
https://user-images.githubusercontent.com/1991296/197385372-962a6dea-bca1-4d50-bf96-1d8c27b98c81.mp4
Or you can even run it straight in the browser: [talk.wasm](examples/talk.wasm)
You can also easily make your own offline voice assistant application:
https://user-images.githubusercontent.com/1991296/204038393-2f846eae-c255-4099-a76d-5735c25c49da.mp4
https://user-images.githubusercontent.com/1991296/203411580-fedb4839-05e4-4474-8364-aaf1e9a9b615.mp4
Or you can even run it straight in the browser: [talk.wasm](examples/talk.wasm)
## Implementation details
@ -100,27 +102,27 @@ c++ -I. -I./examples -O3 -std=c++11 -pthread examples/main/main.cpp whisper.o gg
usage: ./main [options] file0.wav file1.wav ...
options:
-h, --help show this help message and exit
-s SEED, --seed SEED RNG seed (default: -1)
-t N, --threads N number of threads to use during computation (default: 4)
-p N, --processors N number of processors to use during computation (default: 1)
-ot N, --offset-t N time offset in milliseconds (default: 0)
-on N, --offset-n N segment index offset (default: 0)
-mc N, --max-context N maximum number of text context tokens to store (default: max)
-ml N, --max-len N maximum segment length in characters (default: 0)
-wt N, --word-thold N word timestamp probability threshold (default: 0.010000)
-v, --verbose verbose output
--translate translate from source language to english
-otxt, --output-txt output result in a text file
-ovtt, --output-vtt output result in a vtt file
-osrt, --output-srt output result in a srt file
-owts, --output-words output script for generating karaoke video
-ps, --print_special print special tokens
-pc, --print_colors print colors
-nt, --no_timestamps do not print timestamps
-l LANG, --language LANG spoken language (default: en)
-m FNAME, --model FNAME model path (default: models/ggml-base.en.bin)
-f FNAME, --file FNAME input WAV file path
-h, --help [default] show this help message and exit
-t N, --threads N [4 ] number of threads to use during computation
-p N, --processors N [1 ] number of processors to use during computation
-ot N, --offset-t N [0 ] time offset in milliseconds
-on N, --offset-n N [0 ] segment index offset
-d N, --duration N [0 ] duration of audio to process in milliseconds
-mc N, --max-context N [-1 ] maximum number of text context tokens to store
-ml N, --max-len N [0 ] maximum segment length in characters
-wt N, --word-thold N [0.01 ] word timestamp probability threshold
-su, --speed-up [false ] speed up audio by x2 (reduced accuracy)
-tr, --translate [false ] translate from source language to english
-otxt, --output-txt [false ] output result in a text file
-ovtt, --output-vtt [false ] output result in a vtt file
-osrt, --output-srt [false ] output result in a srt file
-owts, --output-words [false ] output script for generating karaoke video
-ps, --print-special [false ] print special tokens
-pc, --print-colors [false ] print colors
-nt, --no-timestamps [true ] do not print timestamps
-l LANG, --language LANG [en ] spoken language
-m FNAME, --model FNAME [models/ggml-base.en.bin] model path
-f FNAME, --file FNAME [ ] input WAV file path
bash ./models/download-ggml-model.sh base.en
Downloading ggml model base.en ...
@ -152,13 +154,13 @@ whisper_model_load: n_text_layer = 6
whisper_model_load: n_mels = 80
whisper_model_load: f16 = 1
whisper_model_load: type = 2
whisper_model_load: mem_required = 670.00 MB
whisper_model_load: adding 1607 extra tokens
whisper_model_load: mem_required = 506.00 MB
whisper_model_load: ggml ctx size = 140.60 MB
whisper_model_load: memory size = 22.83 MB
whisper_model_load: model size = 140.54 MB
system_info: n_threads = 4 / 10 | AVX2 = 0 | AVX512 = 0 | NEON = 1 | FP16_VA = 1 | WASM_SIMD = 0 | BLAS = 1 |
system_info: n_threads = 4 / 10 | AVX = 0 | AVX2 = 0 | AVX512 = 0 | NEON = 1 | FP16_VA = 1 | WASM_SIMD = 0 | BLAS = 1 |
main: processing 'samples/jfk.wav' (176000 samples, 11.0 sec), 4 threads, 1 processors, lang = en, task = transcribe, timestamps = 1 ...

@ -6,10 +6,16 @@
#include <vector>
#include <thread>
std::thread g_worker;
std::vector<struct whisper_context *> g_contexts(4, nullptr);
EMSCRIPTEN_BINDINGS(whisper) {
emscripten::function("init", emscripten::optional_override([](const std::string & path_model) {
if (g_worker.joinable()) {
g_worker.join();
}
for (size_t i = 0; i < g_contexts.size(); ++i) {
if (g_contexts[i] == nullptr) {
g_contexts[i] = whisper_init(path_model.c_str());
@ -25,6 +31,10 @@ EMSCRIPTEN_BINDINGS(whisper) {
}));
emscripten::function("free", emscripten::optional_override([](size_t index) {
if (g_worker.joinable()) {
g_worker.join();
}
--index;
if (index < g_contexts.size()) {
@ -34,6 +44,10 @@ EMSCRIPTEN_BINDINGS(whisper) {
}));
emscripten::function("full_default", emscripten::optional_override([](size_t index, const emscripten::val & audio, const std::string & lang, bool translate) {
if (g_worker.joinable()) {
g_worker.join();
}
--index;
if (index >= g_contexts.size()) {
@ -49,7 +63,7 @@ EMSCRIPTEN_BINDINGS(whisper) {
params.print_realtime = true;
params.print_progress = false;
params.print_timestamps = true;
params.print_special_tokens = false;
params.print_special = false;
params.translate = translate;
params.language = whisper_is_multilingual(g_contexts[index]) ? lang.c_str() : "en";
params.n_threads = std::min(8, (int) std::thread::hardware_concurrency());
@ -80,10 +94,15 @@ EMSCRIPTEN_BINDINGS(whisper) {
printf("\n");
}
int ret = whisper_full(g_contexts[index], params, pcmf32.data(), pcmf32.size());
// run the worker
{
g_worker = std::thread([index, params, pcmf32 = std::move(pcmf32)]() {
whisper_reset_timings(g_contexts[index]);
whisper_full(g_contexts[index], params, pcmf32.data(), pcmf32.size());
whisper_print_timings(g_contexts[index]);
});
}
return ret;
return 0;
}));
}

File diff suppressed because one or more lines are too long

@ -20,9 +20,11 @@ include_directories(${CMAKE_CURRENT_SOURCE_DIR})
if (EMSCRIPTEN)
add_subdirectory(whisper.wasm)
add_subdirectory(stream.wasm)
add_subdirectory(talk.wasm)
else()
add_subdirectory(main)
add_subdirectory(stream)
add_subdirectory(command)
add_subdirectory(bench)
endif()

@ -17,14 +17,13 @@ bool whisper_params_parse(int argc, char ** argv, whisper_params & params) {
for (int i = 1; i < argc; i++) {
std::string arg = argv[i];
if (arg == "-t" || arg == "--threads") {
params.n_threads = std::stoi(argv[++i]);
} else if (arg == "-m" || arg == "--model") {
params.model = argv[++i];
} else if (arg == "-h" || arg == "--help") {
if (arg == "-h" || arg == "--help") {
whisper_print_usage(argc, argv, params);
exit(0);
} else {
}
else if (arg == "-t" || arg == "--threads") { params.n_threads = std::stoi(argv[++i]); }
else if (arg == "-m" || arg == "--model") { params.model = argv[++i]; }
else {
fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
whisper_print_usage(argc, argv, params);
exit(0);
@ -39,9 +38,9 @@ void whisper_print_usage(int argc, char ** argv, const whisper_params & params)
fprintf(stderr, "usage: %s [options]\n", argv[0]);
fprintf(stderr, "\n");
fprintf(stderr, "options:\n");
fprintf(stderr, " -h, --help show this help message and exit\n");
fprintf(stderr, " -t N, --threads N number of threads to use during computation (default: %d)\n", params.n_threads);
fprintf(stderr, " -m FNAME, --model FNAME model path (default: %s)\n", params.model.c_str());
fprintf(stderr, " -h, --help [default] show this help message and exit\n");
fprintf(stderr, " -t N, --threads N [%-7d] number of threads to use during computation\n", params.n_threads);
fprintf(stderr, " -m FNAME, --model FNAME [%-7s] model path\n", params.model.c_str());
fprintf(stderr, "\n");
}

@ -0,0 +1,7 @@
if (WHISPER_SUPPORT_SDL2)
# command
set(TARGET command)
add_executable(${TARGET} command.cpp)
target_include_directories(${TARGET} PRIVATE ${SDL2_INCLUDE_DIRS})
target_link_libraries(${TARGET} PRIVATE whisper ${SDL2_LIBRARIES} ${CMAKE_THREAD_LIBS_INIT})
endif ()

@ -0,0 +1,28 @@
# command
This is a basic Voice Assistant example that accepts voice commands from the microphone.
More info is available in [issue #171](https://github.com/ggerganov/whisper.cpp/issues/171).
```bash
# Run with default arguments and small model
./command -m ./models/ggml-small.en.bin -t 8
# On Raspberry Pi, use tiny or base models + "-ac 768" for better performance
./command -m ./models/ggml-tiny.en.bin -ac 768 -t 4 -c 0
```
https://user-images.githubusercontent.com/1991296/204038393-2f846eae-c255-4099-a76d-5735c25c49da.mp4
## Building
The `command` tool depends on SDL2 library to capture audio from the microphone. You can build it like this:
```bash
# Install SDL2 on Linux
sudo apt-get install libsdl2-dev
# Install SDL2 on Mac OS
brew install sdl2
make command
```

@ -0,0 +1,655 @@
// Voice assistant example
//
// Speak short text commands to the microphone.
// This program will detect your voice command and convert them to text.
//
// ref: https://github.com/ggerganov/whisper.cpp/issues/171
//
#include "whisper.h"
#include <SDL.h>
#include <SDL_audio.h>
#include <cassert>
#include <cstdio>
#include <fstream>
#include <mutex>
#include <regex>
#include <string>
#include <thread>
#include <vector>
// command-line parameters
struct whisper_params {
int32_t n_threads = std::min(4, (int32_t) std::thread::hardware_concurrency());
int32_t prompt_ms = 5000;
int32_t command_ms = 4000;
int32_t capture_id = -1;
int32_t max_tokens = 32;
int32_t audio_ctx = 0;
float vad_thold = 0.6f;
float freq_thold = 100.0f;
bool speed_up = false;
bool translate = false;
bool no_context = true;
bool print_special = false;
bool print_energy = false;
bool no_timestamps = true;
std::string language = "en";
std::string model = "models/ggml-base.en.bin";
std::string fname_out = "";
};
void whisper_print_usage(int argc, char ** argv, const whisper_params & params);
bool whisper_params_parse(int argc, char ** argv, whisper_params & params) {
for (int i = 1; i < argc; i++) {
std::string arg = argv[i];
if (arg == "-h" || arg == "--help") {
whisper_print_usage(argc, argv, params);
exit(0);
}
else if (arg == "-t" || arg == "--threads") { params.n_threads = std::stoi(argv[++i]); }
else if (arg == "-pms" || arg == "--prompt-ms") { params.prompt_ms = std::stoi(argv[++i]); }
else if (arg == "-cms" || arg == "--command-ms") { params.command_ms = std::stoi(argv[++i]); }
else if (arg == "-c" || arg == "--capture") { params.capture_id = std::stoi(argv[++i]); }
else if (arg == "-mt" || arg == "--max-tokens") { params.max_tokens = std::stoi(argv[++i]); }
else if (arg == "-ac" || arg == "--audio-ctx") { params.audio_ctx = std::stoi(argv[++i]); }
else if (arg == "-vth" || arg == "--vad-thold") { params.vad_thold = std::stof(argv[++i]); }
else if (arg == "-fth" || arg == "--freq-thold") { params.freq_thold = std::stof(argv[++i]); }
else if (arg == "-su" || arg == "--speed-up") { params.speed_up = true; }
else if (arg == "-tr" || arg == "--translate") { params.translate = true; }
else if (arg == "-ps" || arg == "--print-special") { params.print_special = true; }
else if (arg == "-pe" || arg == "--print-energy") { params.print_energy = true; }
else if (arg == "-l" || arg == "--language") { params.language = argv[++i]; }
else if (arg == "-m" || arg == "--model") { params.model = argv[++i]; }
else if (arg == "-f" || arg == "--file") { params.fname_out = argv[++i]; }
else {
fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
whisper_print_usage(argc, argv, params);
exit(0);
}
}
return true;
}
void whisper_print_usage(int argc, char ** argv, const whisper_params & params) {
fprintf(stderr, "\n");
fprintf(stderr, "usage: %s [options]\n", argv[0]);
fprintf(stderr, "\n");
fprintf(stderr, "options:\n");
fprintf(stderr, " -h, --help [default] show this help message and exit\n");
fprintf(stderr, " -t N, --threads N [%-7d] number of threads to use during computation\n", params.n_threads);
fprintf(stderr, " -pms N, --prompt-ms N [%-7d] prompt duration in milliseconds\n", params.prompt_ms);
fprintf(stderr, " -cms N, --command-ms N [%-7d] command duration in milliseconds\n", params.command_ms);
fprintf(stderr, " -c ID, --capture ID [%-7d] capture device ID\n", params.capture_id);
fprintf(stderr, " -mt N, --max-tokens N [%-7d] maximum number of tokens per audio chunk\n", params.max_tokens);
fprintf(stderr, " -ac N, --audio-ctx N [%-7d] audio context size (0 - all)\n", params.audio_ctx);
fprintf(stderr, " -vth N, --vad-thold N [%-7.2f] voice activity detection threshold\n", params.vad_thold);
fprintf(stderr, " -fth N, --freq-thold N [%-7.2f] high-pass frequency cutoff\n", params.freq_thold);
fprintf(stderr, " -su, --speed-up [%-7s] speed up audio by x2 (reduced accuracy)\n", params.speed_up ? "true" : "false");
fprintf(stderr, " -tr, --translate [%-7s] translate from source language to english\n", params.translate ? "true" : "false");
fprintf(stderr, " -ps, --print-special [%-7s] print special tokens\n", params.print_special ? "true" : "false");
fprintf(stderr, " -pe, --print-energy [%-7s] print sound energy (for debugging)\n", params.print_energy ? "true" : "false");
fprintf(stderr, " -l LANG, --language LANG [%-7s] spoken language\n", params.language.c_str());
fprintf(stderr, " -m FNAME, --model FNAME [%-7s] model path\n", params.model.c_str());
fprintf(stderr, " -f FNAME, --file FNAME [%-7s] text output file name\n", params.fname_out.c_str());
fprintf(stderr, "\n");
}
//
// SDL Audio capture
//
class audio_async {
public:
audio_async(int len_ms);
~audio_async();
bool init(int capture_id, int sample_rate);
// start capturing audio via the provided SDL callback
// keep last len_ms seconds of audio in a circular buffer
bool resume();
bool pause();
bool clear();
// callback to be called by SDL
void callback(uint8_t * stream, int len);
// get audio data from the circular buffer
void get(int ms, std::vector<float> & audio);
private:
SDL_AudioDeviceID m_dev_id_in = 0;
int m_len_ms = 0;
int m_sample_rate = 0;
bool m_running = false;
std::mutex m_mutex;
std::vector<float> m_audio;
std::vector<float> m_audio_new;
size_t m_audio_pos = 0;
size_t m_audio_len = 0;
};
audio_async::audio_async(int len_ms) {
m_len_ms = len_ms;
}
audio_async::~audio_async() {
if (m_dev_id_in) {
SDL_CloseAudioDevice(m_dev_id_in);
}
}
bool audio_async::init(int capture_id, int sample_rate) {
SDL_LogSetPriority(SDL_LOG_CATEGORY_APPLICATION, SDL_LOG_PRIORITY_INFO);
if (SDL_Init(SDL_INIT_AUDIO) < 0) {
SDL_LogError(SDL_LOG_CATEGORY_APPLICATION, "Couldn't initialize SDL: %s\n", SDL_GetError());
return false;
}
SDL_SetHintWithPriority(SDL_HINT_AUDIO_RESAMPLING_MODE, "medium", SDL_HINT_OVERRIDE);
{
int nDevices = SDL_GetNumAudioDevices(SDL_TRUE);
fprintf(stderr, "%s: found %d capture devices:\n", __func__, nDevices);
for (int i = 0; i < nDevices; i++) {
fprintf(stderr, "%s: - Capture device #%d: '%s'\n", __func__, i, SDL_GetAudioDeviceName(i, SDL_TRUE));
}
}
SDL_AudioSpec capture_spec_requested;
SDL_AudioSpec capture_spec_obtained;
SDL_zero(capture_spec_requested);
SDL_zero(capture_spec_obtained);
capture_spec_requested.freq = sample_rate;
capture_spec_requested.format = AUDIO_F32;
capture_spec_requested.channels = 1;
capture_spec_requested.samples = 1024;
capture_spec_requested.callback = [](void * userdata, uint8_t * stream, int len) {
audio_async * audio = (audio_async *) userdata;
audio->callback(stream, len);
};
capture_spec_requested.userdata = this;
if (capture_id >= 0) {
fprintf(stderr, "%s: attempt to open capture device %d : '%s' ...\n", __func__, capture_id, SDL_GetAudioDeviceName(capture_id, SDL_TRUE));
m_dev_id_in = SDL_OpenAudioDevice(SDL_GetAudioDeviceName(capture_id, SDL_TRUE), SDL_TRUE, &capture_spec_requested, &capture_spec_obtained, 0);
} else {
fprintf(stderr, "%s: attempt to open default capture device ...\n", __func__);
m_dev_id_in = SDL_OpenAudioDevice(nullptr, SDL_TRUE, &capture_spec_requested, &capture_spec_obtained, 0);
}
if (!m_dev_id_in) {
fprintf(stderr, "%s: couldn't open an audio device for capture: %s!\n", __func__, SDL_GetError());
m_dev_id_in = 0;
return false;
} else {
fprintf(stderr, "%s: obtained spec for input device (SDL Id = %d):\n", __func__, m_dev_id_in);
fprintf(stderr, "%s: - sample rate: %d\n", __func__, capture_spec_obtained.freq);
fprintf(stderr, "%s: - format: %d (required: %d)\n", __func__, capture_spec_obtained.format,
capture_spec_requested.format);
fprintf(stderr, "%s: - channels: %d (required: %d)\n", __func__, capture_spec_obtained.channels,
capture_spec_requested.channels);
fprintf(stderr, "%s: - samples per frame: %d\n", __func__, capture_spec_obtained.samples);
}
m_sample_rate = capture_spec_obtained.freq;
m_audio.resize((m_sample_rate*m_len_ms)/1000);
return true;
}
bool audio_async::resume() {
if (!m_dev_id_in) {
fprintf(stderr, "%s: no audio device to resume!\n", __func__);
return false;
}
if (m_running) {
fprintf(stderr, "%s: already running!\n", __func__);
return false;
}
SDL_PauseAudioDevice(m_dev_id_in, 0);
m_running = true;
return true;
}
bool audio_async::pause() {
if (!m_dev_id_in) {
fprintf(stderr, "%s: no audio device to pause!\n", __func__);
return false;
}
if (!m_running) {
fprintf(stderr, "%s: already paused!\n", __func__);
return false;
}
SDL_PauseAudioDevice(m_dev_id_in, 1);
m_running = false;
return true;
}
bool audio_async::clear() {
if (!m_dev_id_in) {
fprintf(stderr, "%s: no audio device to clear!\n", __func__);
return false;
}
if (!m_running) {
fprintf(stderr, "%s: not running!\n", __func__);
return false;
}
{
std::lock_guard<std::mutex> lock(m_mutex);
m_audio_pos = 0;
m_audio_len = 0;
}
return true;
}
// callback to be called by SDL
void audio_async::callback(uint8_t * stream, int len) {
if (!m_running) {
return;
}
const size_t n_samples = len / sizeof(float);
m_audio_new.resize(n_samples);
memcpy(m_audio_new.data(), stream, n_samples * sizeof(float));
//fprintf(stderr, "%s: %zu samples, pos %zu, len %zu\n", __func__, n_samples, m_audio_pos, m_audio_len);
{
std::lock_guard<std::mutex> lock(m_mutex);
if (m_audio_pos + n_samples > m_audio.size()) {
const size_t n0 = m_audio.size() - m_audio_pos;
memcpy(&m_audio[m_audio_pos], stream, n0 * sizeof(float));
memcpy(&m_audio[0], &stream[n0], (n_samples - n0) * sizeof(float));
m_audio_pos = (m_audio_pos + n_samples) % m_audio.size();
m_audio_len = m_audio.size();
} else {
memcpy(&m_audio[m_audio_pos], stream, n_samples * sizeof(float));
m_audio_pos = (m_audio_pos + n_samples) % m_audio.size();
m_audio_len = std::min(m_audio_len + n_samples, m_audio.size());
}
}
}
void audio_async::get(int ms, std::vector<float> & result) {
if (!m_dev_id_in) {
fprintf(stderr, "%s: no audio device to get audio from!\n", __func__);
return;
}
if (!m_running) {
fprintf(stderr, "%s: not running!\n", __func__);
return;
}
result.clear();
{
std::lock_guard<std::mutex> lock(m_mutex);
if (ms <= 0) {
ms = m_len_ms;
}
size_t n_samples = (m_sample_rate * ms) / 1000;
if (n_samples > m_audio_len) {
n_samples = m_audio_len;
}
result.resize(n_samples);
int s0 = m_audio_pos - n_samples;
if (s0 < 0) {
s0 += m_audio.size();
}
if (s0 + n_samples > m_audio.size()) {
const size_t n0 = m_audio.size() - s0;
memcpy(result.data(), &m_audio[s0], n0 * sizeof(float));
memcpy(&result[n0], &m_audio[0], (n_samples - n0) * sizeof(float));
} else {
memcpy(result.data(), &m_audio[s0], n_samples * sizeof(float));
}
}
}
///////////////////////////
std::string trim(const std::string & s) {
std::regex e("^\\s+|\\s+$");
return std::regex_replace(s, e, "");
}
void high_pass_filter(std::vector<float> & data, float cutoff, float sample_rate) {
const float rc = 1.0f / (2.0f * M_PI * cutoff);
const float dt = 1.0f / sample_rate;
const float alpha = dt / (rc + dt);
float y = data[0];
for (size_t i = 1; i < data.size(); i++) {
y = alpha * (y + data[i] - data[i - 1]);
data[i] = y;
}
}
bool vad_simple(std::vector<float> & pcmf32, int sample_rate, int last_ms, float vad_thold, float freq_thold, bool verbose) {
const int n_samples = pcmf32.size();
const int n_samples_last = (sample_rate * last_ms) / 1000;
if (n_samples_last >= n_samples) {
// not enough samples - assume no speech
return false;
}
if (freq_thold > 0.0f) {
high_pass_filter(pcmf32, freq_thold, sample_rate);
}
float energy_all = 0.0f;
float energy_last = 0.0f;
for (size_t i = 0; i < n_samples; i++) {
energy_all += fabsf(pcmf32[i]);
if (i >= n_samples - n_samples_last) {
energy_last += fabsf(pcmf32[i]);
}
}
energy_all /= n_samples;
energy_last /= n_samples_last;
if (verbose) {
fprintf(stderr, "%s: energy_all: %f, energy_last: %f, vad_thold: %f, freq_thold: %f\n", __func__, energy_all, energy_last, vad_thold, freq_thold);
}
if (energy_last > vad_thold*energy_all) {
return false;
}
return true;
}
std::string transcribe(whisper_context * ctx, const whisper_params & params, const std::vector<float> & pcmf32, float & prob, int64_t & t_ms) {
const auto t_start = std::chrono::high_resolution_clock::now();
prob = 0.0f;
t_ms = 0;
whisper_full_params wparams = whisper_full_default_params(WHISPER_SAMPLING_GREEDY);
wparams.print_progress = false;
wparams.print_special = params.print_special;
wparams.print_realtime = false;
wparams.print_timestamps = !params.no_timestamps;
wparams.translate = params.translate;
wparams.no_context = true;
wparams.single_segment = true;
wparams.max_tokens = params.max_tokens;
wparams.language = params.language.c_str();
wparams.n_threads = params.n_threads;
wparams.audio_ctx = params.audio_ctx;
wparams.speed_up = params.speed_up;
if (whisper_full(ctx, wparams, pcmf32.data(), pcmf32.size()) != 0) {
return "";
}
int prob_n = 0;
std::string result;
const int n_segments = whisper_full_n_segments(ctx);
for (int i = 0; i < n_segments; ++i) {
const char * text = whisper_full_get_segment_text(ctx, i);
result += text;
const int n_tokens = whisper_full_n_tokens(ctx, i);
for (int j = 0; j < n_tokens; ++j) {
const auto token = whisper_full_get_token_data(ctx, i, j);
prob += token.p;
++prob_n;
}
}
if (prob_n > 0) {
prob /= prob_n;
}
const auto t_end = std::chrono::high_resolution_clock::now();
t_ms = std::chrono::duration_cast<std::chrono::milliseconds>(t_end - t_start).count();
return result;
}
// compute similarity between two strings using Levenshtein distance
float similarity(const std::string & s0, const std::string & s1) {
const size_t len0 = s0.size() + 1;
const size_t len1 = s1.size() + 1;
std::vector<int> col(len1, 0);
std::vector<int> prevCol(len1, 0);
for (size_t i = 0; i < len1; i++) {
prevCol[i] = i;
}
for (size_t i = 0; i < len0; i++) {
col[0] = i;
for (size_t j = 1; j < len1; j++) {
col[j] = std::min(std::min(1 + col[j - 1], 1 + prevCol[j]), prevCol[j - 1] + (s0[i - 1] == s1[j - 1] ? 0 : 1));
}
col.swap(prevCol);
}
const float dist = prevCol[len1 - 1];
return 1.0f - (dist / std::max(s0.size(), s1.size()));
}
int main(int argc, char ** argv) {
whisper_params params;
if (whisper_params_parse(argc, argv, params) == false) {
return 1;
}
if (whisper_lang_id(params.language.c_str()) == -1) {
fprintf(stderr, "error: unknown language '%s'\n", params.language.c_str());
whisper_print_usage(argc, argv, params);
exit(0);
}
// whisper init
struct whisper_context * ctx = whisper_init(params.model.c_str());
// print some info about the processing
{
fprintf(stderr, "\n");
if (!whisper_is_multilingual(ctx)) {
if (params.language != "en" || params.translate) {
params.language = "en";
params.translate = false;
fprintf(stderr, "%s: WARNING: model is not multilingual, ignoring language and translation options\n", __func__);
}
}
fprintf(stderr, "%s: processing, %d threads, lang = %s, task = %s, timestamps = %d ...\n",
__func__,
params.n_threads,
params.language.c_str(),
params.translate ? "translate" : "transcribe",
params.no_timestamps ? 0 : 1);
fprintf(stderr, "\n");
}
// init audio
audio_async audio(30*1000);
if (!audio.init(params.capture_id, WHISPER_SAMPLE_RATE)) {
fprintf(stderr, "%s: audio.init() failed!\n", __func__);
return 1;
}
audio.resume();
bool is_running = true;
bool have_prompt = false;
bool ask_prompt = true;
float prob0 = 0.0f;
float prob = 0.0f;
std::vector<float> pcmf32_cur;
std::vector<float> pcmf32_prompt;
const std::string k_prompt = "Ok Whisper, start listening for commands.";
// main loop
while (is_running) {
// handle Ctrl + C
{
SDL_Event event;
while (SDL_PollEvent(&event)) {
switch (event.type) {
case SDL_QUIT:
{
is_running = false;
} break;
default:
break;
}
}
if (!is_running) {
break;
}
}
// delay
std::this_thread::sleep_for(std::chrono::milliseconds(100));
if (ask_prompt) {
fprintf(stdout, "\n");
fprintf(stdout, "%s: Say the following phrase: '%s%s%s'\n", __func__, "\033[1m", k_prompt.c_str(), "\033[0m");
fprintf(stdout, "\n");
ask_prompt = false;
}
int64_t t_ms = 0;
{
audio.get(2000, pcmf32_cur);
if (vad_simple(pcmf32_cur, WHISPER_SAMPLE_RATE, 1000, params.vad_thold, params.freq_thold, params.print_energy)) {
fprintf(stdout, "%s: Speech detected! Processing ...\n", __func__);
if (!have_prompt) {
audio.get(params.prompt_ms, pcmf32_cur);
const auto txt = ::trim(::transcribe(ctx, params, pcmf32_cur, prob0, t_ms));
fprintf(stdout, "%s: Heard '%s%s%s', (t = %d ms)\n", __func__, "\033[1m", txt.c_str(), "\033[0m", (int) t_ms);
const float sim = similarity(txt, k_prompt);
if (txt.length() < 0.8*k_prompt.length() || txt.length() > 1.2*k_prompt.length() || sim < 0.8f) {
fprintf(stdout, "%s: WARNING: prompt not recognized, try again\n", __func__);
ask_prompt = true;
} else {
fprintf(stdout, "\n");
fprintf(stdout, "%s: The prompt has been recognized!\n", __func__);
fprintf(stdout, "%s: Waiting for voice commands ...\n", __func__);
fprintf(stdout, "\n");
// save the audio for the prompt
pcmf32_prompt = pcmf32_cur;
have_prompt = true;
}
} else {
audio.get(params.command_ms, pcmf32_cur);
// prepend the prompt audio
pcmf32_cur.insert(pcmf32_cur.begin(), pcmf32_prompt.begin(), pcmf32_prompt.end());
const auto txt = ::trim(::transcribe(ctx, params, pcmf32_cur, prob, t_ms));
prob = 100.0f*(prob - prob0);
//fprintf(stdout, "%s: heard '%s'\n", __func__, txt.c_str());
// find the prompt in the text
float best_sim = 0.0f;
size_t best_len = 0;
for (int n = 0.8*k_prompt.size(); n <= 1.2*k_prompt.size(); ++n) {
const auto prompt = txt.substr(0, n);
const float sim = similarity(prompt, k_prompt);
//fprintf(stderr, "%s: prompt = '%s', sim = %f\n", __func__, prompt.c_str(), sim);
if (sim > best_sim) {
best_sim = sim;
best_len = n;
}
}
const std::string command = ::trim(txt.substr(best_len));
fprintf(stdout, "%s: Command '%s%s%s', (t = %d ms)\n", __func__, "\033[1m", command.c_str(), "\033[0m", (int) t_ms);
fprintf(stdout, "\n");
}
audio.clear();
}
}
}
audio.pause();
whisper_print_timings(ctx);
whisper_free(ctx);
return 0;
}

@ -0,0 +1,182 @@
// Common Javascript functions used by the examples
function convertTypedArray(src, type) {
var buffer = new ArrayBuffer(src.byteLength);
var baseView = new src.constructor(buffer).set(src);
return new type(buffer);
}
var printTextarea = (function() {
var element = document.getElementById('output');
if (element) element.alue = ''; // clear browser cache
return function(text) {
if (arguments.length > 1) text = Array.prototype.slice.call(arguments).join(' ');
console.log(text);
if (element) {
element.value += text + "\n";
element.scrollTop = element.scrollHeight; // focus on bottom
}
};
})();
async function clearCache() {
if (confirm('Are you sure you want to clear the cache?\nAll the models will be downloaded again.')) {
indexedDB.deleteDatabase(dbName);
}
}
// fetch a remote file from remote URL using the Fetch API
async function fetchRemote(url, cbProgress, cbPrint) {
cbPrint('fetchRemote: downloading with fetch()...');
const response = await fetch(
url,
{
method: 'GET',
headers: {
'Content-Type': 'application/octet-stream',
},
}
);
if (!response.ok) {
cbPrint('fetchRemote: failed to fetch ' + url);
return;
}
const contentLength = response.headers.get('content-length');
const total = parseInt(contentLength, 10);
const reader = response.body.getReader();
var chunks = [];
var receivedLength = 0;
var progressLast = -1;
while (true) {
const { done, value } = await reader.read();
if (done) {
break;
}
chunks.push(value);
receivedLength += value.length;
if (contentLength) {
cbProgress(receivedLength/total);
var progressCur = Math.round((receivedLength / total) * 10);
if (progressCur != progressLast) {
cbPrint('fetchRemote: fetching ' + 10*progressCur + '% ...');
progressLast = progressCur;
}
}
}
var position = 0;
var chunksAll = new Uint8Array(receivedLength);
for (var chunk of chunks) {
chunksAll.set(chunk, position);
position += chunk.length;
}
return chunksAll;
}
// load remote data
// - check if the data is already in the IndexedDB
// - if not, fetch it from the remote URL and store it in the IndexedDB
function loadRemote(url, dst, size_mb, cbProgress, cbReady, cbCancel, cbPrint) {
// query the storage quota and print it
navigator.storage.estimate().then(function (estimate) {
cbPrint('loadRemote: storage quota: ' + estimate.quota + ' bytes');
cbPrint('loadRemote: storage usage: ' + estimate.usage + ' bytes');
});
// check if the data is already in the IndexedDB
var rq = indexedDB.open(dbName, dbVersion);
rq.onupgradeneeded = function (event) {
var db = event.target.result;
if (db.version == 1) {
var os = db.createObjectStore('models', { autoIncrement: false });
cbPrint('loadRemote: created IndexedDB ' + db.name + ' version ' + db.version);
} else {
// clear the database
var os = event.currentTarget.transaction.objectStore('models');
os.clear();
cbPrint('loadRemote: cleared IndexedDB ' + db.name + ' version ' + db.version);
}
};
rq.onsuccess = function (event) {
var db = event.target.result;
var tx = db.transaction(['models'], 'readonly');
var os = tx.objectStore('models');
var rq = os.get(url);
rq.onsuccess = function (event) {
if (rq.result) {
cbPrint('loadRemote: "' + url + '" is already in the IndexedDB');
cbReady(dst, rq.result);
} else {
// data is not in the IndexedDB
cbPrint('loadRemote: "' + url + '" is not in the IndexedDB');
// alert and ask the user to confirm
if (!confirm(
'You are about to download ' + size_mb + ' MB of data.\n' +
'The model data will be cached in the browser for future use.\n\n' +
'Press OK to continue.')) {
cbCancel();
return;
}
fetchRemote(url, cbProgress, cbPrint).then(function (data) {
if (data) {
// store the data in the IndexedDB
var rq = indexedDB.open(dbName, dbVersion);
rq.onsuccess = function (event) {
var db = event.target.result;
var tx = db.transaction(['models'], 'readwrite');
var os = tx.objectStore('models');
var rq = os.put(data, url);
rq.onsuccess = function (event) {
cbPrint('loadRemote: "' + url + '" stored in the IndexedDB');
cbReady(dst, data);
};
rq.onerror = function (event) {
cbPrint('loadRemote: failed to store "' + url + '" in the IndexedDB');
cbCancel();
};
};
}
});
}
};
rq.onerror = function (event) {
cbPrint('loadRemote: failed to get data from the IndexedDB');
cbCancel();
};
};
rq.onerror = function (event) {
cbPrint('loadRemote: failed to open IndexedDB');
cbCancel();
};
rq.onblocked = function (event) {
cbPrint('loadRemote: failed to open IndexedDB: blocked');
cbCancel();
};
rq.onabort = function (event) {
cbPrint('loadRemote: failed to open IndexedDB: abort');
};
}

@ -6,29 +6,28 @@ It can be used as a reference for using the `whisper.cpp` library in other proje
```
./main -h
usage: ./bin/main [options] file0.wav file1.wav ...
-h, --help show this help message and exit
-s SEED, --seed SEED RNG seed (default: -1)
-t N, --threads N number of threads to use during computation (default: 4)
-p N, --processors N number of processors to use during computation (default: 1)
-ot N, --offset-t N time offset in milliseconds (default: 0)
-on N, --offset-n N segment index offset (default: 0)
-mc N, --max-context N maximum number of text context tokens to store (default: max)
-ml N, --max-len N maximum segment length in characters (default: 0)
-wt N, --word-thold N word timestamp probability threshold (default: 0.010000)
-v, --verbose verbose output
--translate translate from source language to english
-otxt, --output-txt output result in a text file
-ovtt, --output-vtt output result in a vtt file
-osrt, --output-srt output result in a srt file
-owts, --output-words output script for generating karaoke video
-ps, --print_special print special tokens
-pc, --print_colors print colors
-nt, --no_timestamps do not print timestamps
-l LANG, --language LANG spoken language (default: en)
-m FNAME, --model FNAME model path (default: models/ggml-base.en.bin)
-f FNAME, --file FNAME input WAV file path
-h, --help show this help message and exit
usage: ./main [options] file0.wav file1.wav ...
options:
-h, --help [default] show this help message and exit
-t N, --threads N [4 ] number of threads to use during computation
-p N, --processors N [1 ] number of processors to use during computation
-ot N, --offset-t N [0 ] time offset in milliseconds
-on N, --offset-n N [0 ] segment index offset
-d N, --duration N [0 ] duration of audio to process in milliseconds
-mc N, --max-context N [-1 ] maximum number of text context tokens to store
-ml N, --max-len N [0 ] maximum segment length in characters
-wt N, --word-thold N [0.01 ] word timestamp probability threshold
-su, --speed-up [false ] speed up audio by x2 (reduced accuracy)
-tr, --translate [false ] translate from source language to english
-otxt, --output-txt [false ] output result in a text file
-ovtt, --output-vtt [false ] output result in a vtt file
-osrt, --output-srt [false ] output result in a srt file
-owts, --output-words [false ] output script for generating karaoke video
-ps, --print-special [false ] print special tokens
-pc, --print-colors [false ] print colors
-nt, --no-timestamps [true ] do not print timestamps
-l LANG, --language LANG [en ] spoken language
-m FNAME, --model FNAME [models/ggml-base.en.bin] model path
-f FNAME, --file FNAME [ ] input WAV file path
```

@ -36,6 +36,10 @@ std::string to_timestamp(int64_t t, bool comma = false) {
return std::string(buf);
}
int timestamp_to_sample(int64_t t, int n_samples) {
return std::max(0, std::min((int) n_samples - 1, (int) ((t*WHISPER_SAMPLE_RATE)/100)));
}
// helper function to replace substrings
void replace_all(std::string & s, const std::string & search, const std::string & replace) {
for (size_t pos = 0; ; pos += replace.length()) {
@ -48,7 +52,6 @@ void replace_all(std::string & s, const std::string & search, const std::string
// command-line parameters
struct whisper_params {
int32_t seed = -1; // RNG seed, not used currently
int32_t n_threads = std::min(4, (int32_t) std::thread::hardware_concurrency());
int32_t n_processors = 1;
int32_t offset_t_ms = 0;
@ -60,13 +63,13 @@ struct whisper_params {
float word_thold = 0.01f;
bool speed_up = false;
bool verbose = false;
bool translate = false;
bool diarize = false;
bool output_txt = false;
bool output_vtt = false;
bool output_srt = false;
bool output_wts = false;
bool print_special_tokens = false;
bool print_special = false;
bool print_colors = false;
bool no_timestamps = false;
@ -87,59 +90,32 @@ bool whisper_params_parse(int argc, char ** argv, whisper_params & params) {
continue;
}
if (arg == "-s" || arg == "--seed") {
params.seed = std::stoi(argv[++i]);
} else if (arg == "-t" || arg == "--threads") {
params.n_threads = std::stoi(argv[++i]);
} else if (arg == "-p" || arg == "--processors") {
params.n_processors = std::stoi(argv[++i]);
} else if (arg == "-ot" || arg == "--offset-t") {
params.offset_t_ms = std::stoi(argv[++i]);
} else if (arg == "-on" || arg == "--offset-n") {
params.offset_n = std::stoi(argv[++i]);
} else if (arg == "-d" || arg == "--duration") {
params.duration_ms = std::stoi(argv[++i]);
} else if (arg == "-mc" || arg == "--max-context") {
params.max_context = std::stoi(argv[++i]);
} else if (arg == "-ml" || arg == "--max-len") {
params.max_len = std::stoi(argv[++i]);
} else if (arg == "-wt" || arg == "--word-thold") {
params.word_thold = std::stof(argv[++i]);
} else if (arg == "-su" || arg == "--speed-up") {
params.speed_up = true;
} else if (arg == "-v" || arg == "--verbose") {
params.verbose = true;
} else if (arg == "--translate") {
params.translate = true;
} else if (arg == "-l" || arg == "--language") {
params.language = argv[++i];
if (whisper_lang_id(params.language.c_str()) == -1) {
fprintf(stderr, "error: unknown language '%s'\n", params.language.c_str());
if (arg == "-h" || arg == "--help") {
whisper_print_usage(argc, argv, params);
exit(0);
}
} else if (arg == "-otxt" || arg == "--output-txt") {
params.output_txt = true;
} else if (arg == "-ovtt" || arg == "--output-vtt") {
params.output_vtt = true;
} else if (arg == "-osrt" || arg == "--output-srt") {
params.output_srt = true;
} else if (arg == "-owts" || arg == "--output-words") {
params.output_wts = true;
} else if (arg == "-ps" || arg == "--print_special") {
params.print_special_tokens = true;
} else if (arg == "-pc" || arg == "--print_colors") {
params.print_colors = true;
} else if (arg == "-nt" || arg == "--no_timestamps") {
params.no_timestamps = true;
} else if (arg == "-m" || arg == "--model") {
params.model = argv[++i];
} else if (arg == "-f" || arg == "--file") {
params.fname_inp.push_back(argv[++i]);
} else if (arg == "-h" || arg == "--help") {
whisper_print_usage(argc, argv, params);
exit(0);
} else {
else if (arg == "-t" || arg == "--threads") { params.n_threads = std::stoi(argv[++i]); }
else if (arg == "-p" || arg == "--processors") { params.n_processors = std::stoi(argv[++i]); }
else if (arg == "-ot" || arg == "--offset-t") { params.offset_t_ms = std::stoi(argv[++i]); }
else if (arg == "-on" || arg == "--offset-n") { params.offset_n = std::stoi(argv[++i]); }
else if (arg == "-d" || arg == "--duration") { params.duration_ms = std::stoi(argv[++i]); }
else if (arg == "-mc" || arg == "--max-context") { params.max_context = std::stoi(argv[++i]); }
else if (arg == "-ml" || arg == "--max-len") { params.max_len = std::stoi(argv[++i]); }
else if (arg == "-wt" || arg == "--word-thold") { params.word_thold = std::stof(argv[++i]); }
else if (arg == "-su" || arg == "--speed-up") { params.speed_up = true; }
else if (arg == "-tr" || arg == "--translate") { params.translate = true; }
else if (arg == "-di" || arg == "--diarize") { params.diarize = true; }
else if (arg == "-otxt" || arg == "--output-txt") { params.output_txt = true; }
else if (arg == "-ovtt" || arg == "--output-vtt") { params.output_vtt = true; }
else if (arg == "-osrt" || arg == "--output-srt") { params.output_srt = true; }
else if (arg == "-owts" || arg == "--output-words") { params.output_wts = true; }
else if (arg == "-ps" || arg == "--print-special") { params.print_special = true; }
else if (arg == "-pc" || arg == "--print-colors") { params.print_colors = true; }
else if (arg == "-nt" || arg == "--no-timestamps") { params.no_timestamps = true; }
else if (arg == "-l" || arg == "--language") { params.language = argv[++i]; }
else if (arg == "-m" || arg == "--model") { params.model = argv[++i]; }
else if (arg == "-f" || arg == "--file") { params.fname_inp.push_back(argv[++i]); }
else {
fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
whisper_print_usage(argc, argv, params);
exit(0);
@ -154,34 +130,40 @@ void whisper_print_usage(int argc, char ** argv, const whisper_params & params)
fprintf(stderr, "usage: %s [options] file0.wav file1.wav ...\n", argv[0]);
fprintf(stderr, "\n");
fprintf(stderr, "options:\n");
fprintf(stderr, " -h, --help show this help message and exit\n");
fprintf(stderr, " -s SEED, --seed SEED RNG seed (default: -1)\n");
fprintf(stderr, " -t N, --threads N number of threads to use during computation (default: %d)\n", params.n_threads);
fprintf(stderr, " -p N, --processors N number of processors to use during computation (default: %d)\n", params.n_processors);
fprintf(stderr, " -ot N, --offset-t N time offset in milliseconds (default: %d)\n", params.offset_t_ms);
fprintf(stderr, " -on N, --offset-n N segment index offset (default: %d)\n", params.offset_n);
fprintf(stderr, " -d N, --duration N duration of audio to process in milliseconds (default: %d)\n", params.duration_ms);
fprintf(stderr, " -mc N, --max-context N maximum number of text context tokens to store (default: max)\n");
fprintf(stderr, " -ml N, --max-len N maximum segment length in characters (default: %d)\n", params.max_len);
fprintf(stderr, " -wt N, --word-thold N word timestamp probability threshold (default: %f)\n", params.word_thold);
fprintf(stderr, " -su, --speed-up speed up audio by factor of 2 (faster processing, reduced accuracy, default: %s)\n", params.speed_up ? "true" : "false");
fprintf(stderr, " -v, --verbose verbose output\n");
fprintf(stderr, " --translate translate from source language to english\n");
fprintf(stderr, " -otxt, --output-txt output result in a text file\n");
fprintf(stderr, " -ovtt, --output-vtt output result in a vtt file\n");
fprintf(stderr, " -osrt, --output-srt output result in a srt file\n");
fprintf(stderr, " -owts, --output-words output script for generating karaoke video\n");
fprintf(stderr, " -ps, --print_special print special tokens\n");
fprintf(stderr, " -pc, --print_colors print colors\n");
fprintf(stderr, " -nt, --no_timestamps do not print timestamps\n");
fprintf(stderr, " -l LANG, --language LANG spoken language (default: %s)\n", params.language.c_str());
fprintf(stderr, " -m FNAME, --model FNAME model path (default: %s)\n", params.model.c_str());
fprintf(stderr, " -f FNAME, --file FNAME input WAV file path\n");
fprintf(stderr, " -h, --help [default] show this help message and exit\n");
fprintf(stderr, " -t N, --threads N [%-7d] number of threads to use during computation\n", params.n_threads);
fprintf(stderr, " -p N, --processors N [%-7d] number of processors to use during computation\n", params.n_processors);
fprintf(stderr, " -ot N, --offset-t N [%-7d] time offset in milliseconds\n", params.offset_t_ms);
fprintf(stderr, " -on N, --offset-n N [%-7d] segment index offset\n", params.offset_n);
fprintf(stderr, " -d N, --duration N [%-7d] duration of audio to process in milliseconds\n", params.duration_ms);
fprintf(stderr, " -mc N, --max-context N [%-7d] maximum number of text context tokens to store\n", params.max_context);
fprintf(stderr, " -ml N, --max-len N [%-7d] maximum segment length in characters\n", params.max_len);
fprintf(stderr, " -wt N, --word-thold N [%-7.2f] word timestamp probability threshold\n", params.word_thold);
fprintf(stderr, " -su, --speed-up [%-7s] speed up audio by x2 (reduced accuracy)\n", params.speed_up ? "true" : "false");
fprintf(stderr, " -tr, --translate [%-7s] translate from source language to english\n", params.translate ? "true" : "false");
fprintf(stderr, " -di, --diarize [%-7s] stereo audio diarization\n", params.diarize ? "true" : "false");
fprintf(stderr, " -otxt, --output-txt [%-7s] output result in a text file\n", params.output_txt ? "true" : "false");
fprintf(stderr, " -ovtt, --output-vtt [%-7s] output result in a vtt file\n", params.output_vtt ? "true" : "false");
fprintf(stderr, " -osrt, --output-srt [%-7s] output result in a srt file\n", params.output_srt ? "true" : "false");
fprintf(stderr, " -owts, --output-words [%-7s] output script for generating karaoke video\n", params.output_wts ? "true" : "false");
fprintf(stderr, " -ps, --print-special [%-7s] print special tokens\n", params.print_special ? "true" : "false");
fprintf(stderr, " -pc, --print-colors [%-7s] print colors\n", params.print_colors ? "true" : "false");
fprintf(stderr, " -nt, --no-timestamps [%-7s] do not print timestamps\n", params.no_timestamps ? "false" : "true");
fprintf(stderr, " -l LANG, --language LANG [%-7s] spoken language\n", params.language.c_str());
fprintf(stderr, " -m FNAME, --model FNAME [%-7s] model path\n", params.model.c_str());
fprintf(stderr, " -f FNAME, --file FNAME [%-7s] input WAV file path\n", "");
fprintf(stderr, "\n");
}
struct whisper_print_user_data {
const whisper_params * params;
const std::vector<std::vector<float>> * pcmf32s;
};
void whisper_print_segment_callback(struct whisper_context * ctx, int n_new, void * user_data) {
const whisper_params & params = *(whisper_params *) user_data;
const auto & params = *((whisper_print_user_data *) user_data)->params;
const auto & pcmf32s = *((whisper_print_user_data *) user_data)->pcmf32s;
const int n_segments = whisper_full_n_segments(ctx);
@ -195,7 +177,7 @@ void whisper_print_segment_callback(struct whisper_context * ctx, int n_new, voi
if (params.no_timestamps) {
if (params.print_colors) {
for (int j = 0; j < whisper_full_n_tokens(ctx, i); ++j) {
if (params.print_special_tokens == false) {
if (params.print_special == false) {
const whisper_token id = whisper_full_get_token_id(ctx, i, j);
if (id >= whisper_token_eot(ctx)) {
continue;
@ -218,10 +200,37 @@ void whisper_print_segment_callback(struct whisper_context * ctx, int n_new, voi
const int64_t t0 = whisper_full_get_segment_t0(ctx, i);
const int64_t t1 = whisper_full_get_segment_t1(ctx, i);
std::string speaker = "";
if (params.diarize && pcmf32s.size() == 2) {
const int64_t n_samples = pcmf32s[0].size();
const int64_t is0 = timestamp_to_sample(t0, n_samples);
const int64_t is1 = timestamp_to_sample(t1, n_samples);
double energy0 = 0.0f;
double energy1 = 0.0f;
for (int64_t j = is0; j < is1; j++) {
energy0 += fabs(pcmf32s[0][j]);
energy1 += fabs(pcmf32s[1][j]);
}
if (energy0 > 1.1*energy1) {
speaker = "(speaker 0)";
} else if (energy1 > 1.1*energy0) {
speaker = "(speaker 1)";
} else {
speaker = "(speaker ?)";
}
//printf("is0 = %lld, is1 = %lld, energy0 = %f, energy1 = %f, %s\n", is0, is1, energy0, energy1, speaker.c_str());
}
if (params.print_colors) {
printf("[%s --> %s] ", to_timestamp(t0).c_str(), to_timestamp(t1).c_str());
for (int j = 0; j < whisper_full_n_tokens(ctx, i); ++j) {
if (params.print_special_tokens == false) {
if (params.print_special == false) {
const whisper_token id = whisper_full_get_token_id(ctx, i, j);
if (id >= whisper_token_eot(ctx)) {
continue;
@ -233,13 +242,13 @@ void whisper_print_segment_callback(struct whisper_context * ctx, int n_new, voi
const int col = std::max(0, std::min((int) k_colors.size(), (int) (std::pow(p, 3)*float(k_colors.size()))));
printf("%s%s%s", k_colors[col].c_str(), text, "\033[0m");
printf("%s%s%s%s", speaker.c_str(), k_colors[col].c_str(), text, "\033[0m");
}
printf("\n");
} else {
const char * text = whisper_full_get_segment_text(ctx, i);
printf("[%s --> %s] %s\n", to_timestamp(t0).c_str(), to_timestamp(t1).c_str(), text);
printf("[%s --> %s] %s%s\n", to_timestamp(t0).c_str(), to_timestamp(t1).c_str(), speaker.c_str(), text);
}
}
}
@ -267,7 +276,7 @@ bool output_vtt(struct whisper_context * ctx, const char * fname) {
std::ofstream fout(fname);
if (!fout.is_open()) {
fprintf(stderr, "%s: failed to open '%s' for writing\n", __func__, fname);
return 9;
return false;
}
fprintf(stderr, "%s: saving output to '%s'\n", __func__, fname);
@ -432,16 +441,18 @@ int main(int argc, char ** argv) {
return 1;
}
if (params.seed < 0) {
params.seed = time(NULL);
}
if (params.fname_inp.empty()) {
fprintf(stderr, "error: no input files specified\n");
whisper_print_usage(argc, argv, params);
return 2;
}
if (whisper_lang_id(params.language.c_str()) == -1) {
fprintf(stderr, "error: unknown language '%s'\n", params.language.c_str());
whisper_print_usage(argc, argv, params);
exit(0);
}
// whisper init
struct whisper_context * ctx = whisper_init(params.model.c_str());
@ -454,53 +465,60 @@ int main(int argc, char ** argv) {
for (int f = 0; f < (int) params.fname_inp.size(); ++f) {
const auto fname_inp = params.fname_inp[f];
std::vector<float> pcmf32; // mono-channel F32 PCM
std::vector<std::vector<float>> pcmf32s; // stereo-channel F32 PCM
// WAV input
std::vector<float> pcmf32;
{
drwav wav;
std::vector<uint8_t> wav_data; // used for pipe input from stdin
if (fname_inp == "-") {
std::vector<uint8_t> wav_data;
{
uint8_t buf[1024];
while (true)
{
const size_t n = fread(buf, 1, sizeof(buf), stdin);
if (n == 0)
{
if (n == 0) {
break;
}
wav_data.insert(wav_data.end(), buf, buf + n);
}
}
if (drwav_init_memory(&wav, wav_data.data(), wav_data.size(), NULL) == false)
{
if (drwav_init_memory(&wav, wav_data.data(), wav_data.size(), NULL) == false) {
fprintf(stderr, "error: failed to open WAV file from stdin\n");
return 4;
}
fprintf(stderr, "%s: read %zu bytes from stdin\n", __func__, wav_data.size());
}
else if (drwav_init_file(&wav, fname_inp.c_str(), NULL) == false) {
fprintf(stderr, "error: failed to open '%s' as WAV file\n", fname_inp.c_str());
return 4;
return 5;
}
if (wav.channels != 1 && wav.channels != 2) {
fprintf(stderr, "%s: WAV file '%s' must be mono or stereo\n", argv[0], fname_inp.c_str());
return 5;
return 6;
}
if (params.diarize && wav.channels != 2 && params.no_timestamps == false) {
fprintf(stderr, "%s: WAV file '%s' must be stereo for diarization and timestamps have to be enabled\n", argv[0], fname_inp.c_str());
return 6;
}
if (wav.sampleRate != WHISPER_SAMPLE_RATE) {
fprintf(stderr, "%s: WAV file '%s' must be 16 kHz\n", argv[0], fname_inp.c_str());
return 6;
return 8;
}
if (wav.bitsPerSample != 16) {
fprintf(stderr, "%s: WAV file '%s' must be 16-bit\n", argv[0], fname_inp.c_str());
return 7;
return 9;
}
int n = wav.totalPCMFrameCount;
const uint64_t n = wav_data.empty() ? wav.totalPCMFrameCount : wav_data.size()/(wav.channels*wav.bitsPerSample/8);
std::vector<int16_t> pcm16;
pcm16.resize(n*wav.channels);
@ -518,6 +536,18 @@ int main(int argc, char ** argv) {
pcmf32[i] = float(pcm16[2*i] + pcm16[2*i + 1])/65536.0f;
}
}
if (params.diarize) {
// convert to stereo, float
pcmf32s.resize(2);
pcmf32s[0].resize(n);
pcmf32s[1].resize(n);
for (int i = 0; i < n; i++) {
pcmf32s[0][i] = float(pcm16[2*i])/32768.0f;
pcmf32s[1][i] = float(pcm16[2*i + 1])/32768.0f;
}
}
}
// print system information
@ -555,7 +585,7 @@ int main(int argc, char ** argv) {
wparams.print_realtime = false;
wparams.print_progress = false;
wparams.print_timestamps = !params.no_timestamps;
wparams.print_special_tokens = params.print_special_tokens;
wparams.print_special = params.print_special;
wparams.translate = params.translate;
wparams.language = params.language.c_str();
wparams.n_threads = params.n_threads;
@ -569,15 +599,17 @@ int main(int argc, char ** argv) {
wparams.speed_up = params.speed_up;
whisper_print_user_data user_data = { &params, &pcmf32s };
// this callback is called on each new segment
if (!wparams.print_realtime) {
wparams.new_segment_callback = whisper_print_segment_callback;
wparams.new_segment_callback_user_data = &params;
wparams.new_segment_callback_user_data = &user_data;
}
if (whisper_full_parallel(ctx, wparams, pcmf32.data(), pcmf32.size(), params.n_processors) != 0) {
fprintf(stderr, "%s: failed to process audio\n", argv[0]);
return 8;
return 10;
}
}

@ -0,0 +1,47 @@
#
# libstream
#
set(TARGET libstream)
add_executable(${TARGET}
emscripten.cpp
)
target_link_libraries(${TARGET} PRIVATE
whisper
)
unset(EXTRA_FLAGS)
if (WHISPER_WASM_SINGLE_FILE)
set(EXTRA_FLAGS "-s SINGLE_FILE=1")
message(STATUS "Embedding WASM inside stream.js")
add_custom_command(
TARGET ${TARGET} POST_BUILD
COMMAND ${CMAKE_COMMAND} -E copy
${CMAKE_BINARY_DIR}/bin/libstream.js
${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/stream.wasm/stream.js
)
endif()
set_target_properties(${TARGET} PROPERTIES LINK_FLAGS " \
--bind \
-s USE_PTHREADS=1 \
-s PTHREAD_POOL_SIZE=8 \
-s INITIAL_MEMORY=1024MB \
-s TOTAL_MEMORY=1024MB \
-s FORCE_FILESYSTEM=1 \
-s EXPORTED_RUNTIME_METHODS=\"['print', 'printErr', 'ccall', 'cwrap']\" \
${EXTRA_FLAGS} \
")
#
# stream.wasm
#
set(TARGET stream.wasm)
configure_file(${CMAKE_CURRENT_SOURCE_DIR}/index-tmpl.html ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/${TARGET}/index.html @ONLY)
configure_file(${CMAKE_CURRENT_SOURCE_DIR}/../helpers.js ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/${TARGET}/helpers.js @ONLY)

@ -0,0 +1,20 @@
# stream.wasm
Real-time transcription in the browser using WebAssembly
Online demo: https://whisper.ggerganov.com/stream/
## Build instructions
```bash
# build using Emscripten (v3.1.2)
git clone https://github.com/ggerganov/whisper.cpp
cd whisper.cpp
mkdir build-em && cd build-em
emcmake cmake ..
make -j
# copy the produced page to your HTTP path
cp bin/stream.wasm/* /path/to/html/
cp bin/libstream.worker.js /path/to/html/
```

@ -0,0 +1,213 @@
#include "ggml.h"
#include "whisper.h"
#include <emscripten.h>
#include <emscripten/bind.h>
#include <atomic>
#include <cmath>
#include <mutex>
#include <string>
#include <thread>
#include <vector>
constexpr int N_THREAD = 8;
std::vector<struct whisper_context *> g_contexts(4, nullptr);
std::mutex g_mutex;
std::thread g_worker;
std::atomic<bool> g_running(false);
std::string g_status = "";
std::string g_status_forced = "";
std::string g_transcribed = "";
std::vector<float> g_pcmf32;
void stream_set_status(const std::string & status) {
std::lock_guard<std::mutex> lock(g_mutex);
g_status = status;
}
void stream_main(size_t index) {
stream_set_status("loading data ...");
struct whisper_full_params wparams = whisper_full_default_params(whisper_sampling_strategy::WHISPER_SAMPLING_GREEDY);
wparams.n_threads = std::min(N_THREAD, (int) std::thread::hardware_concurrency());
wparams.offset_ms = 0;
wparams.translate = false;
wparams.no_context = true;
wparams.single_segment = true;
wparams.print_realtime = false;
wparams.print_progress = false;
wparams.print_timestamps = true;
wparams.print_special = false;
wparams.max_tokens = 32;
wparams.audio_ctx = 768; // partial encoder context for better performance
wparams.language = "en";
printf("stream: using %d threads\n", N_THREAD);
std::vector<float> pcmf32;
// whisper context
auto & ctx = g_contexts[index];
// 5 seconds interval
const int64_t window_samples = 5*WHISPER_SAMPLE_RATE;
while (g_running) {
stream_set_status("waiting for audio ...");
{
std::unique_lock<std::mutex> lock(g_mutex);
if (g_pcmf32.size() < 1024) {
lock.unlock();
std::this_thread::sleep_for(std::chrono::milliseconds(10));
continue;
}
pcmf32 = std::vector<float>(g_pcmf32.end() - std::min((int64_t) g_pcmf32.size(), window_samples), g_pcmf32.end());
g_pcmf32.clear();
}
{
const auto t_start = std::chrono::high_resolution_clock::now();
stream_set_status("running whisper ...");
int ret = whisper_full(ctx, wparams, pcmf32.data(), pcmf32.size());
if (ret != 0) {
printf("whisper_full() failed: %d\n", ret);
break;
}
const auto t_end = std::chrono::high_resolution_clock::now();
printf("stream: whisper_full() returned %d in %f seconds\n", ret, std::chrono::duration<double>(t_end - t_start).count());
}
{
std::string text_heard;
{
const int n_segments = whisper_full_n_segments(ctx);
for (int i = n_segments - 1; i < n_segments; ++i) {
const char * text = whisper_full_get_segment_text(ctx, i);
const int64_t t0 = whisper_full_get_segment_t0(ctx, i);
const int64_t t1 = whisper_full_get_segment_t1(ctx, i);
printf("transcribed: %s\n", text);
text_heard += text;
}
}
{
std::lock_guard<std::mutex> lock(g_mutex);
g_transcribed = text_heard;
}
}
}
if (index < g_contexts.size()) {
whisper_free(g_contexts[index]);
g_contexts[index] = nullptr;
}
}
EMSCRIPTEN_BINDINGS(stream) {
emscripten::function("init", emscripten::optional_override([](const std::string & path_model) {
for (size_t i = 0; i < g_contexts.size(); ++i) {
if (g_contexts[i] == nullptr) {
g_contexts[i] = whisper_init(path_model.c_str());
if (g_contexts[i] != nullptr) {
g_running = true;
if (g_worker.joinable()) {
g_worker.join();
}
g_worker = std::thread([i]() {
stream_main(i);
});
return i + 1;
} else {
return (size_t) 0;
}
}
}
return (size_t) 0;
}));
emscripten::function("free", emscripten::optional_override([](size_t index) {
if (g_running) {
g_running = false;
}
}));
emscripten::function("set_audio", emscripten::optional_override([](size_t index, const emscripten::val & audio) {
--index;
if (index >= g_contexts.size()) {
return -1;
}
if (g_contexts[index] == nullptr) {
return -2;
}
{
std::lock_guard<std::mutex> lock(g_mutex);
const int n = audio["length"].as<int>();
emscripten::val heap = emscripten::val::module_property("HEAPU8");
emscripten::val memory = heap["buffer"];
g_pcmf32.resize(n);
emscripten::val memoryView = audio["constructor"].new_(memory, reinterpret_cast<uintptr_t>(g_pcmf32.data()), n);
memoryView.call<void>("set", audio);
}
return 0;
}));
emscripten::function("get_transcribed", emscripten::optional_override([]() {
std::string transcribed;
{
std::lock_guard<std::mutex> lock(g_mutex);
transcribed = std::move(g_transcribed);
}
return transcribed;
}));
emscripten::function("get_status", emscripten::optional_override([]() {
std::string status;
{
std::lock_guard<std::mutex> lock(g_mutex);
status = g_status_forced.empty() ? g_status : g_status_forced;
}
return status;
}));
emscripten::function("set_status", emscripten::optional_override([](const std::string & status) {
{
std::lock_guard<std::mutex> lock(g_mutex);
g_status_forced = status;
}
}));
}

@ -0,0 +1,385 @@
<!doctype html>
<html lang="en-us">
<head>
<title>stream : Real-time Whisper transcription in WebAssembly</title>
<style>
#output {
width: 100%;
height: 100%;
margin: 0 auto;
margin-top: 10px;
border-left: 0px;
border-right: 0px;
padding-left: 0px;
padding-right: 0px;
display: block;
background-color: black;
color: white;
font-size: 10px;
font-family: 'Lucida Console', Monaco, monospace;
outline: none;
white-space: pre;
overflow-wrap: normal;
overflow-x: scroll;
}
</style>
</head>
<body>
<div id="main-container">
<b>stream : Real-time Whisper transcription in WebAssembly</b>
<br><br>
You can find more about this project on <a href="https://github.com/ggerganov/whisper.cpp/tree/master/examples/stream.wasm">GitHub</a>.
<br><br>
<hr>
Select the model you would like to use, click the "Start" button and start speaking
<br><br>
<div id="model-whisper">
Whisper model: <span id="model-whisper-status"></span>
<button id="fetch-whisper-tiny-en" onclick="loadWhisper('tiny.en')">tiny.en (75 MB)</button>
<button id="fetch-whisper-base-en" onclick="loadWhisper('base.en')">base.en (142 MB)</button>
<span id="fetch-whisper-progress"></span>
<!--
<input type="file" id="file" name="file" onchange="loadFile(event, 'whisper.bin')" />
-->
</div>
<br>
<div id="input">
<button id="start" onclick="onStart()" disabled>Start</button>
<button id="stop" onclick="onStop()" disabled>Stop</button>
<button id="clear" onclick="clearCache()">Clear Cache</button>
</div>
<br>
<div id="state">
Status: <b><span id="state-status">not started</span></b>
<pre id="state-transcribed">[The transcribed text will be displayed here]</pre>
</div>
<hr>
Debug output:
<textarea id="output" rows="20"></textarea>
<br>
<b>Troubleshooting</b>
<br><br>
The page does some heavy computations, so make sure:
<ul>
<li>To use a modern web browser (e.g. Chrome, Firefox)</li>
<li>To use a fast desktop or laptop computer (i.e. not a mobile phone)</li>
<li>Your browser supports WASM <a href="https://webassembly.org/roadmap/">Fixed-width SIMD</a></li>
</ul>
<div class="cell-version">
<span>
|
Build time: <span class="nav-link">@GIT_DATE@</span> |
Commit hash: <a class="nav-link" href="https://github.com/ggerganov/whisper.cpp/commit/@GIT_SHA1@">@GIT_SHA1@</a> |
Commit subject: <span class="nav-link">@GIT_COMMIT_SUBJECT@</span> |
<a class="nav-link" href="https://github.com/ggerganov/whisper.cpp/tree/master/examples/stream.wasm">Source Code</a> |
</span>
</div>
</div>
<script type="text/javascript" src="helpers.js"></script>
<script type='text/javascript'>
const kRestartRecording_s = 15;
const kSampleRate = 16000;
window.AudioContext = window.AudioContext || window.webkitAudioContext;
window.OfflineAudioContext = window.OfflineAudioContext || window.webkitOfflineAudioContext;
// web audio context
var context = null;
// audio data
var audio = null;
var audio0 = null;
// the stream instance
var instance = null;
// model name
var model_whisper = null;
var Module = {
print: printTextarea,
printErr: printTextarea,
setStatus: function(text) {
printTextarea('js: ' + text);
},
monitorRunDependencies: function(left) {
},
preRun: function() {
printTextarea('js: Preparing ...');
},
postRun: function() {
printTextarea('js: Initialized successfully!');
}
};
//
// fetch models
//
let dbVersion = 1
let dbName = 'whisper.ggerganov.com';
let indexedDB = window.indexedDB || window.mozIndexedDB || window.webkitIndexedDB || window.msIndexedDB
function storeFS(fname, buf) {
// write to WASM file using FS_createDataFile
// if the file exists, delete it
try {
Module.FS_unlink(fname);
} catch (e) {
// ignore
}
Module.FS_createDataFile("/", fname, buf, true, true);
printTextarea('storeFS: stored model: ' + fname + ' size: ' + buf.length);
document.getElementById('model-whisper-status').innerHTML = 'loaded "' + model_whisper + '"!';
if (model_whisper != null) {
document.getElementById('start').disabled = false;
document.getElementById('stop' ).disabled = true;
}
}
function loadWhisper(model) {
let urls = {
'tiny.en': 'https://whisper.ggerganov.com/ggml-model-whisper-tiny.en.bin',
'base.en': 'https://whisper.ggerganov.com/ggml-model-whisper-base.en.bin',
};
let sizes = {
'tiny.en': 75,
'base.en': 142,
};
let url = urls[model];
let dst = 'whisper.bin';
let size_mb = sizes[model];
model_whisper = model;
document.getElementById('fetch-whisper-tiny-en').style.display = 'none';
document.getElementById('fetch-whisper-base-en').style.display = 'none';
document.getElementById('model-whisper-status').innerHTML = 'loading "' + model + '" ... ';
cbProgress = function(p) {
let el = document.getElementById('fetch-whisper-progress');
el.innerHTML = Math.round(100*p) + '%';
};
cbCancel = function() {
var el;
el = document.getElementById('fetch-whisper-tiny-en'); if (el) el.style.display = 'inline-block';
el = document.getElementById('fetch-whisper-base-en'); if (el) el.style.display = 'inline-block';
el = document.getElementById('model-whisper-status'); if (el) el.innerHTML = '';
};
loadRemote(url, dst, size_mb, cbProgress, storeFS, cbCancel, printTextarea);
}
//
// microphone
//
var mediaRecorder = null;
var doRecording = false;
var startTime = 0;
function stopRecording() {
Module.set_status("paused");
doRecording = false;
audio0 = null;
audio = null;
context = null;
}
function startRecording() {
if (!context) {
context = new AudioContext({
sampleRate: 16000,
channelCount: 1,
echoCancellation: false,
autoGainControl: true,
noiseSuppression: true,
});
}
Module.set_status("");
document.getElementById('start').disabled = true;
document.getElementById('stop').disabled = false;
doRecording = true;
startTime = Date.now();
var chunks = [];
var stream = null;
navigator.mediaDevices.getUserMedia({audio: true, video: false})
.then(function(s) {
stream = s;
mediaRecorder = new MediaRecorder(stream);
mediaRecorder.ondataavailable = function(e) {
chunks.push(e.data);
var blob = new Blob(chunks, { 'type' : 'audio/ogg; codecs=opus' });
var reader = new FileReader();
reader.onload = function(event) {
var buf = new Uint8Array(reader.result);
if (!context) {
return;
}
context.decodeAudioData(buf.buffer, function(audioBuffer) {
var offlineContext = new OfflineAudioContext(audioBuffer.numberOfChannels, audioBuffer.length, audioBuffer.sampleRate);
var source = offlineContext.createBufferSource();
source.buffer = audioBuffer;
source.connect(offlineContext.destination);
source.start(0);
offlineContext.startRendering().then(function(renderedBuffer) {
audio = renderedBuffer.getChannelData(0);
//printTextarea('js: audio recorded, size: ' + audio.length + ', old size: ' + (audio0 == null ? 0 : audio0.length));
var audioAll = new Float32Array(audio0 == null ? audio.length : audio0.length + audio.length);
if (audio0 != null) {
audioAll.set(audio0, 0);
}
audioAll.set(audio, audio0 == null ? 0 : audio0.length);
if (instance) {
Module.set_audio(instance, audioAll);
}
});
}, function(e) {
audio = null;
});
}
reader.readAsArrayBuffer(blob);
};
mediaRecorder.onstop = function(e) {
if (doRecording) {
setTimeout(function() {
startRecording();
});
}
};
mediaRecorder.start(5000);
})
.catch(function(err) {
printTextarea('js: error getting audio stream: ' + err);
});
var interval = setInterval(function() {
if (!doRecording) {
clearInterval(interval);
mediaRecorder.stop();
stream.getTracks().forEach(function(track) {
track.stop();
});
document.getElementById('start').disabled = false;
document.getElementById('stop').disabled = true;
mediaRecorder = null;
}
// if audio length is more than kRestartRecording_s seconds, restart recording
if (audio != null && audio.length > kSampleRate*kRestartRecording_s) {
if (doRecording) {
//printTextarea('js: restarting recording');
clearInterval(interval);
audio0 = audio;
audio = null;
mediaRecorder.stop();
stream.getTracks().forEach(function(track) {
track.stop();
});
}
}
}, 250);
}
//
// main
//
var nLines = 0;
var intervalUpdate = null;
var transcribedAll = '';
function onStart() {
if (!instance) {
instance = Module.init('whisper.bin');
if (instance) {
printTextarea("js: whisper initialized, instance: " + instance);
}
}
if (!instance) {
printTextarea("js: failed to initialize whisper");
return;
}
startRecording();
intervalUpdate = setInterval(function() {
var transcribed = Module.get_transcribed();
if (transcribed != null && transcribed.length > 1) {
transcribedAll += transcribed + '<br>';
nLines++;
// if more than 10 lines, remove the first line
if (nLines > 10) {
var i = transcribedAll.indexOf('<br>');
if (i > 0) {
transcribedAll = transcribedAll.substring(i + 4);
nLines--;
}
}
}
document.getElementById('state-status').innerHTML = Module.get_status();
document.getElementById('state-transcribed').innerHTML = transcribedAll;
}, 100);
}
function onStop() {
stopRecording();
}
</script>
<script type="text/javascript" src="stream.js"></script>
</body>
</html>

@ -21,3 +21,7 @@ brew install sdl2
make stream
```
## Web version
This tool can also run in the browser: [examples/stream.wasm](/examples/stream.wasm)

@ -4,11 +4,6 @@
#include "whisper.h"
// third-party utilities
// use your favorite implementations
#define DR_WAV_IMPLEMENTATION
#include "dr_wav.h"
#include <SDL.h>
#include <SDL_audio.h>
@ -35,7 +30,6 @@ std::string to_timestamp(int64_t t) {
// command-line parameters
struct whisper_params {
int32_t seed = -1; // RNG seed, not used currently
int32_t n_threads = std::min(4, (int32_t) std::thread::hardware_concurrency());
int32_t step_ms = 3000;
int32_t length_ms = 10000;
@ -44,10 +38,9 @@ struct whisper_params {
int32_t audio_ctx = 0;
bool speed_up = false;
bool verbose = false;
bool translate = false;
bool no_context = true;
bool print_special_tokens = false;
bool print_special = false;
bool no_timestamps = true;
std::string language = "en";
@ -61,47 +54,24 @@ bool whisper_params_parse(int argc, char ** argv, whisper_params & params) {
for (int i = 1; i < argc; i++) {
std::string arg = argv[i];
if (arg == "-s" || arg == "--seed") {
params.seed = std::stoi(argv[++i]);
} else if (arg == "-t" || arg == "--threads") {
params.n_threads = std::stoi(argv[++i]);
} else if (arg == "--step") {
params.step_ms = std::stoi(argv[++i]);
} else if (arg == "--length") {
params.length_ms = std::stoi(argv[++i]);
} else if (arg == "-c" || arg == "--capture") {
params.capture_id = std::stoi(argv[++i]);
} else if (arg == "-mt" || arg == "--max_tokens") {
params.max_tokens = std::stoi(argv[++i]);
} else if (arg == "-ac" || arg == "--audio_ctx") {
params.audio_ctx = std::stoi(argv[++i]);
} else if (arg == "-su" || arg == "--speed-up") {
params.speed_up = true;
} else if (arg == "-v" || arg == "--verbose") {
params.verbose = true;
} else if (arg == "--translate") {
params.translate = true;
} else if (arg == "-kc" || arg == "--keep-context") {
params.no_context = false;
} else if (arg == "-l" || arg == "--language") {
params.language = argv[++i];
if (whisper_lang_id(params.language.c_str()) == -1) {
fprintf(stderr, "error: unknown language '%s'\n", params.language.c_str());
if (arg == "-h" || arg == "--help") {
whisper_print_usage(argc, argv, params);
exit(0);
}
} else if (arg == "-ps" || arg == "--print_special") {
params.print_special_tokens = true;
} else if (arg == "-nt" || arg == "--no_timestamps") {
params.no_timestamps = true;
} else if (arg == "-m" || arg == "--model") {
params.model = argv[++i];
} else if (arg == "-f" || arg == "--file") {
params.fname_out = argv[++i];
} else if (arg == "-h" || arg == "--help") {
whisper_print_usage(argc, argv, params);
exit(0);
} else {
else if (arg == "-t" || arg == "--threads") { params.n_threads = std::stoi(argv[++i]); }
else if ( arg == "--step") { params.step_ms = std::stoi(argv[++i]); }
else if ( arg == "--length") { params.length_ms = std::stoi(argv[++i]); }
else if (arg == "-c" || arg == "--capture") { params.capture_id = std::stoi(argv[++i]); }
else if (arg == "-mt" || arg == "--max-tokens") { params.max_tokens = std::stoi(argv[++i]); }
else if (arg == "-ac" || arg == "--audio-ctx") { params.audio_ctx = std::stoi(argv[++i]); }
else if (arg == "-su" || arg == "--speed-up") { params.speed_up = true; }
else if (arg == "-tr" || arg == "--translate") { params.translate = true; }
else if (arg == "-kc" || arg == "--keep-context") { params.no_context = false; }
else if (arg == "-ps" || arg == "--print-special") { params.print_special = true; }
else if (arg == "-l" || arg == "--language") { params.language = argv[++i]; }
else if (arg == "-m" || arg == "--model") { params.model = argv[++i]; }
else if (arg == "-f" || arg == "--file") { params.fname_out = argv[++i]; }
else {
fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
whisper_print_usage(argc, argv, params);
exit(0);
@ -116,23 +86,20 @@ void whisper_print_usage(int argc, char ** argv, const whisper_params & params)
fprintf(stderr, "usage: %s [options]\n", argv[0]);
fprintf(stderr, "\n");
fprintf(stderr, "options:\n");
fprintf(stderr, " -h, --help show this help message and exit\n");
fprintf(stderr, " -s SEED, --seed SEED RNG seed (default: -1)\n");
fprintf(stderr, " -t N, --threads N number of threads to use during computation (default: %d)\n", params.n_threads);
fprintf(stderr, " --step N audio step size in milliseconds (default: %d)\n", params.step_ms);
fprintf(stderr, " --length N audio length in milliseconds (default: %d)\n", params.length_ms);
fprintf(stderr, " -c ID, --capture ID capture device ID (default: -1)\n");
fprintf(stderr, " -mt N, --max_tokens N maximum number of tokens per audio chunk (default: %d)\n", params.max_tokens);
fprintf(stderr, " -ac N, --audio_ctx N audio context size (default: %d, 0 - all)\n", params.audio_ctx);
fprintf(stderr, " -su, --speed-up speed up audio by factor of 2 (faster processing, reduced accuracy, default: %s)\n", params.speed_up ? "true" : "false");
fprintf(stderr, " -v, --verbose verbose output\n");
fprintf(stderr, " --translate translate from source language to english\n");
fprintf(stderr, " -kc, --keep-context keep text context from earlier audio (default: false)\n");
fprintf(stderr, " -ps, --print_special print special tokens\n");
fprintf(stderr, " -nt, --no_timestamps do not print timestamps\n");
fprintf(stderr, " -l LANG, --language LANG spoken language (default: %s)\n", params.language.c_str());
fprintf(stderr, " -m FNAME, --model FNAME model path (default: %s)\n", params.model.c_str());
fprintf(stderr, " -f FNAME, --file FNAME text output file name (default: no output to file)\n");
fprintf(stderr, " -h, --help [default] show this help message and exit\n");
fprintf(stderr, " -t N, --threads N [%-7d] number of threads to use during computation\n", params.n_threads);
fprintf(stderr, " --step N [%-7d] audio step size in milliseconds\n", params.step_ms);
fprintf(stderr, " --length N [%-7d] audio length in milliseconds\n", params.length_ms);
fprintf(stderr, " -c ID, --capture ID [%-7d] capture device ID\n", params.capture_id);
fprintf(stderr, " -mt N, --max-tokens N [%-7d] maximum number of tokens per audio chunk\n", params.max_tokens);
fprintf(stderr, " -ac N, --audio-ctx N [%-7d] audio context size (0 - all)\n", params.audio_ctx);
fprintf(stderr, " -su, --speed-up [%-7s] speed up audio by x2 (reduced accuracy)\n", params.speed_up ? "true" : "false");
fprintf(stderr, " -tr, --translate [%-7s] translate from source language to english\n", params.translate ? "true" : "false");
fprintf(stderr, " -kc, --keep-context [%-7s] keep context between audio chunks\n", params.no_context ? "false" : "true");
fprintf(stderr, " -ps, --print-special [%-7s] print special tokens\n", params.print_special ? "true" : "false");
fprintf(stderr, " -l LANG, --language LANG [%-7s] spoken language\n", params.language.c_str());
fprintf(stderr, " -m FNAME, --model FNAME [%-7s] model path\n", params.model.c_str());
fprintf(stderr, " -f FNAME, --file FNAME [%-7s] text output file name\n", params.fname_out.c_str());
fprintf(stderr, "\n");
}
@ -148,7 +115,6 @@ bool audio_sdl_init(const int capture_id) {
return false;
}
if (g_dev_id_in == 0) {
SDL_LogSetPriority(SDL_LOG_CATEGORY_APPLICATION, SDL_LOG_PRIORITY_INFO);
if (SDL_Init(SDL_INIT_AUDIO) < 0) {
@ -165,9 +131,7 @@ bool audio_sdl_init(const int capture_id) {
fprintf(stderr, "%s: - Capture device #%d: '%s'\n", __func__, i, SDL_GetAudioDeviceName(i, SDL_TRUE));
}
}
}
if (g_dev_id_in == 0) {
SDL_AudioSpec capture_spec_requested;
SDL_AudioSpec capture_spec_obtained;
@ -196,8 +160,6 @@ bool audio_sdl_init(const int capture_id) {
fprintf(stderr, "%s: - channels: %d (required: %d)\n", __func__, capture_spec_obtained.channels, capture_spec_requested.channels);
fprintf(stderr, "%s: - samples per frame: %d\n", __func__, capture_spec_obtained.samples);
}
}
return true;
}
@ -211,10 +173,6 @@ int main(int argc, char ** argv) {
return 1;
}
if (params.seed < 0) {
params.seed = time(NULL);
}
// init audio
if (!audio_sdl_init(params.capture_id)) {
@ -222,6 +180,12 @@ int main(int argc, char ** argv) {
return 1;
}
if (whisper_lang_id(params.language.c_str()) == -1) {
fprintf(stderr, "error: unknown language '%s'\n", params.language.c_str());
whisper_print_usage(argc, argv, params);
exit(0);
}
// whisper init
struct whisper_context * ctx = whisper_init(params.model.c_str());
@ -280,7 +244,8 @@ int main(int argc, char ** argv) {
// main audio loop
while (is_running) {
// process SDL events:
// handle Ctrl + C
{
SDL_Event event;
while (SDL_PollEvent(&event)) {
switch (event.type) {
@ -296,6 +261,11 @@ int main(int argc, char ** argv) {
if (!is_running) {
break;
}
}
if (!is_running) {
break;
}
// process new audio
if (n_iter > 0 && SDL_GetQueuedAudioSize(g_dev_id_in) > 2*n_samples*sizeof(float)) {
@ -332,7 +302,7 @@ int main(int argc, char ** argv) {
whisper_full_params wparams = whisper_full_default_params(WHISPER_SAMPLING_GREEDY);
wparams.print_progress = false;
wparams.print_special_tokens = params.print_special_tokens;
wparams.print_special = params.print_special;
wparams.print_realtime = false;
wparams.print_timestamps = !params.no_timestamps;
wparams.translate = params.translate;
@ -414,6 +384,10 @@ int main(int argc, char ** argv) {
}
}
if (g_dev_id_in >= 0) {
SDL_CloseAudioDevice(g_dev_id_in);
}
whisper_print_timings(ctx);
whisper_free(ctx);

@ -45,3 +45,4 @@ set_target_properties(${TARGET} PROPERTIES LINK_FLAGS " \
set(TARGET talk.wasm)
configure_file(${CMAKE_CURRENT_SOURCE_DIR}/index-tmpl.html ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/${TARGET}/index.html @ONLY)
configure_file(${CMAKE_CURRENT_SOURCE_DIR}/../helpers.js ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/${TARGET}/helpers.js @ONLY)

@ -2,9 +2,9 @@
Talk with an Artificial Intelligence in your browser:
https://user-images.githubusercontent.com/1991296/203411580-fedb4839-05e4-4474-8364-aaf1e9a9b615.mp4
[https://user-images.githubusercontent.com/1991296/203411580-fedb4839-05e4-4474-8364-aaf1e9a9b615.mp4](https://user-images.githubusercontent.com/1991296/203845553-f7b44e13-9a15-4fc8-b518-ae8f4c6770fe.mp4)
Online demo: https://talk.ggerganov.com
Online demo: https://whisper.ggerganov.com/talk/
## How it works?
@ -50,6 +50,21 @@ on a phone or a tablet. Hopefully, in the near future this will become supported
- Better UI (contributions are welcome)
- Better GPT-2 prompting
## Build instructions
```bash
# build using Emscripten (v3.1.2)
git clone https://github.com/ggerganov/whisper.cpp
cd whisper.cpp
mkdir build-em && cd build-em
emcmake cmake ..
make -j
# copy the produced page to your HTTP path
cp bin/talk.wasm/* /path/to/html/
cp bin/libtalk.worker.js /path/to/html/
```
## Feedback
If you have any comments or ideas for improvement, please drop a comment in the following discussion:

@ -59,10 +59,10 @@ void talk_main(size_t index) {
wparams.print_realtime = false;
wparams.print_progress = false;
wparams.print_timestamps = true;
wparams.print_special_tokens = false;
wparams.print_special = false;
wparams.max_tokens = 32;
wparams.audio_ctx = 768;
wparams.audio_ctx = 768; // partial encoder context for better performance
wparams.language = "en";
@ -76,8 +76,8 @@ void talk_main(size_t index) {
auto & ctx = g_contexts[index];
const int64_t step_samples = 2*WHISPER_SAMPLE_RATE;
const int64_t step_ms = (step_samples*1000)/WHISPER_SAMPLE_RATE;
const int64_t window_samples = 9*WHISPER_SAMPLE_RATE;
const int64_t step_ms = (step_samples*1000)/WHISPER_SAMPLE_RATE;
auto t_last = std::chrono::high_resolution_clock::now();
@ -111,7 +111,7 @@ void talk_main(size_t index) {
pcmf32 = std::vector<float>(g_pcmf32.end() - std::min((int64_t) g_pcmf32.size(), window_samples), g_pcmf32.end());
}
// if energy in during last second is above threshold, then skip
// VAD: if energy in during last second is above threshold, then skip
{
float energy_all = 0.0f;
float energy_1s = 0.0f;
@ -133,13 +133,11 @@ void talk_main(size_t index) {
}
}
talk_set_status("processing ...");
g_force_speak = false;
talk_set_status("processing audio (whisper)...");
t_last = t_now;
{
if (!g_force_speak) {
const auto t_start = std::chrono::high_resolution_clock::now();
int ret = whisper_full(ctx, wparams, pcmf32.data(), pcmf32.size());
@ -156,6 +154,7 @@ void talk_main(size_t index) {
{
std::string text_heard;
if (!g_force_speak) {
const int n_segments = whisper_full_n_segments(ctx);
for (int i = n_segments - 1; i < n_segments; ++i) {
const char * text = whisper_full_get_segment_text(ctx, i);
@ -167,6 +166,9 @@ void talk_main(size_t index) {
text_heard += text;
}
}
g_force_speak = false;
// remove text between brackets using regex
{
@ -190,7 +192,7 @@ void talk_main(size_t index) {
text_heard = std::regex_replace(text_heard, std::regex("^\\s+"), "");
text_heard = std::regex_replace(text_heard, std::regex("\\s+$"), "");
talk_set_status("'" + text_heard + "' - thinking how to respond ...");
talk_set_status("'" + text_heard + "' - thinking how to respond (gpt-2) ...");
const std::vector<gpt_vocab::id> tokens = gpt2_tokenize(g_gpt2, text_heard.c_str());

@ -812,9 +812,9 @@ I'm fine, thanks. How are you?
Thanks, I'm fine too. What are you doing?
I'm just sitting here.
It's a lovely day, isn't it?
Yes, it is.
Did you know that I'm a robot?
I wasn't aware of that.
Yes, it is. I love the weather this time of year.
I wish it would rain a little bit.
Me too.
)";
std::mt19937 rng;

@ -35,7 +35,7 @@
<ul>
<li><a href="https://github.com/ggerganov/whisper.cpp">OpenAI's Whisper</a> to listen to you as you speak in the microphone</li>
<li><a href="https://github.com/ggerganov/ggml/tree/master/examples/gpt-2">OpenAI's GPT-2</a> to generate text responses</li>
<li><a href="https://github.com/ggerganov/whisper.cpp/tree/master/examples/talk.wasm">OpenAI's GPT-2</a> to generate text responses</li>
<li><a href="https://developer.mozilla.org/en-US/docs/Web/API/Web_Speech_API">Web Speech API</a> to vocalize the responses through your speakers</li>
</ul>
@ -51,7 +51,7 @@
<br><br>
<div id="model-whisper">
<span id="model-whisper-status">Whisper model:</span>
Whisper model: <span id="model-whisper-status"></span>
<button id="fetch-whisper-tiny-en" onclick="loadWhisper('tiny.en')">tiny.en (75 MB)</button>
<button id="fetch-whisper-base-en" onclick="loadWhisper('base.en')">base.en (142 MB)</button>
<span id="fetch-whisper-progress"></span>
@ -64,7 +64,7 @@
<br>
<div id="model-gpt-2">
<span id="model-gpt-2-status">GPT-2 model:</span>
GPT-2 model: <span id="model-gpt-2-status"></span>
<button id="fetch-gpt-2-small" onclick="loadGPT2('small')">small 117M (240 MB)</button>
<!--<button id="fetch-gpt-2-medium" onclick="loadGPT2('medium')">medium 345M (720 MB)</button>-->
<span id="fetch-gpt-2-progress"></span>
@ -143,7 +143,7 @@
<br><br>
Here is a short video of the demo in action: <a href="https://youtu.be/2om-7tFMaNs">https://youtu.be/2om-7tFMaNs</a>
Here is a short video of the demo in action: <a href="https://youtu.be/LeWKl8t1-Hc">https://youtu.be/LeWKl8t1-Hc</a>
<br><br>
@ -158,20 +158,8 @@
</div>
</div>
<script type="text/javascript" src="helpers.js"></script>
<script type='text/javascript'>
var printTextarea = (function() {
var element = document.getElementById('output');
if (element) element.alue = ''; // clear browser cache
return function(text) {
if (arguments.length > 1) text = Array.prototype.slice.call(arguments).join(' ');
console.log(text);
if (element) {
element.value += text + "\n";
element.scrollTop = element.scrollHeight; // focus on bottom
}
};
})();
const kRestartRecording_s = 15;
const kSampleRate = 16000;
@ -218,6 +206,7 @@
if (voices.length == 0) {
el.innerHTML = '<option value="0">No voices available</option>';
} else {
// populate voice list
var n = 0;
voices.forEach(function(voice, i) {
if (!voice.lang.startsWith('en')) return;
@ -245,17 +234,14 @@
}
};
// helper function
function convertTypedArray(src, type) {
var buffer = new ArrayBuffer(src.byteLength);
var baseView = new src.constructor(buffer).set(src);
return new type(buffer);
}
//
// fetch models
//
let dbVersion = 1
let dbName = 'whisper.ggerganov.com';
let indexedDB = window.indexedDB || window.mozIndexedDB || window.webkitIndexedDB || window.msIndexedDB
function storeFS(fname, buf) {
// write to WASM file using FS_createDataFile
// if the file exists, delete it
@ -267,180 +253,25 @@
Module.FS_createDataFile("/", fname, buf, true, true);
printTextarea('js: stored model: ' + fname + ' size: ' + buf.length);
printTextarea('storeFS: stored model: ' + fname + ' size: ' + buf.length);
if (fname == 'whisper.bin') {
document.getElementById('model-whisper').innerHTML = 'Whisper model: loaded "' + model_whisper + '"!';
document.getElementById('model-whisper-status').innerHTML = 'loaded "' + model_whisper + '"!';
} else if (fname == 'gpt-2.bin') {
document.getElementById('model-gpt-2').innerHTML = 'GPT-2 model: loaded "' + model_gpt_2 + '"!';
document.getElementById('model-gpt-2-status').innerHTML = 'loaded "' + model_gpt_2 + '"!';
}
if (model_whisper != null && model_gpt_2 != null) {
document.getElementById('start').disabled = false;
document.getElementById('stop').disabled = false;
document.getElementById('stop' ).disabled = false;
document.getElementById('voice').disabled = false;
}
}
let dbVersion = 1
let dbName = 'talk.ggerganov.com';
let indexedDB = window.indexedDB || window.mozIndexedDB || window.webkitIndexedDB || window.msIndexedDB
// fetch a remote file from remote URL using the Fetch API
async function fetchRemote(url, elProgress) {
printTextarea('js: downloading with fetch()...');
const response = await fetch(
url,
{
method: 'GET',
headers: {
'Content-Type': 'application/octet-stream',
},
}
);
if (!response.ok) {
printTextarea('js: failed to fetch ' + url);
return;
}
const contentLength = response.headers.get('content-length');
const total = parseInt(contentLength, 10);
const reader = response.body.getReader();
var chunks = [];
var receivedLength = 0;
var progressLast = -1;
while (true) {
const { done, value } = await reader.read();
if (done) {
break;
}
chunks.push(value);
receivedLength += value.length;
if (contentLength) {
// update progress bar element with the new percentage
elProgress.innerHTML = Math.round((receivedLength / total) * 100) + '%';
var progressCur = Math.round((receivedLength / total) * 10);
if (progressCur != progressLast) {
printTextarea('js: fetching ' + 10*progressCur + '% ...');
progressLast = progressCur;
}
}
}
var chunksAll = new Uint8Array(receivedLength);
var position = 0;
for (var chunk of chunks) {
chunksAll.set(chunk, position);
position += chunk.length;
}
return chunksAll;
}
// load remote data
// - check if the data is already in the IndexedDB
// - if not, fetch it from the remote URL and store it in the IndexedDB
// - store it in WASM memory
function loadRemote(url, dst, elProgress, size_mb) {
// query the storage quota and print it
navigator.storage.estimate().then(function (estimate) {
printTextarea('js: storage quota: ' + estimate.quota + ' bytes');
printTextarea('js: storage usage: ' + estimate.usage + ' bytes');
});
// check if the data is already in the IndexedDB
var request = indexedDB.open(dbName, dbVersion);
request.onupgradeneeded = function (event) {
var db = event.target.result;
if (db.version == 1) {
var objectStore = db.createObjectStore('models', { autoIncrement: false });
printTextarea('js: created IndexedDB ' + db.name + ' version ' + db.version);
} else {
// clear the database
var objectStore = event.currentTarget.transaction.objectStore('models');
objectStore.clear();
printTextarea('js: cleared IndexedDB ' + db.name + ' version ' + db.version);
}
};
request.onsuccess = function (event) {
var db = event.target.result;
var transaction = db.transaction(['models'], 'readonly');
var objectStore = transaction.objectStore('models');
var request = objectStore.get(url);
request.onsuccess = function (event) {
if (request.result) {
printTextarea('js: "' + url + '" is already in the IndexedDB');
storeFS(dst, request.result);
} else {
// data is not in the IndexedDB
printTextarea('js: "' + url + '" is not in the IndexedDB');
// alert and ask the user to confirm
if (!confirm('You are about to download ' + size_mb + ' MB of data.\nThe model data will be cached in the browser for future use.\n\nPress OK to continue.')) {
var el;
el = document.getElementById('fetch-whisper-tiny-en'); if (el) el.style.display = 'inline-block';
el = document.getElementById('fetch-whisper-base-en'); if (el) el.style.display = 'inline-block';
el = document.getElementById('fetch-gpt-2-small') ; if (el) el.style.display = 'inline-block';
return;
}
fetchRemote(url, elProgress).then(function (data) {
if (data) {
// store the data in the IndexedDB
var request = indexedDB.open(dbName, dbVersion);
request.onsuccess = function (event) {
var db = event.target.result;
var transaction = db.transaction(['models'], 'readwrite');
var objectStore = transaction.objectStore('models');
var request = objectStore.put(data, url);
request.onsuccess = function (event) {
printTextarea('js: "' + url + '" stored in the IndexedDB');
storeFS(dst, data);
};
request.onerror = function (event) {
printTextarea('js: failed to store "' + url + '" in the IndexedDB');
};
};
}
});
}
};
request.onerror = function (event) {
printTextarea('js: failed to get data from the IndexedDB');
};
};
request.onerror = function (event) {
printTextarea('js: failed to open IndexedDB');
};
request.onblocked = function (event) {
printTextarea('js: failed to open IndexedDB: blocked');
};
request.onabort = function (event) {
printTextarea('js: failed to open IndexedDB: abort');
};
}
function loadWhisper(model) {
let urls = {
'tiny.en': 'https://talk.ggerganov.com/ggml-model-whisper-tiny.en.bin',
'base.en': 'https://talk.ggerganov.com/ggml-model-whisper-base.en.bin',
'tiny.en': 'https://whisper.ggerganov.com/ggml-model-whisper-tiny.en.bin',
'base.en': 'https://whisper.ggerganov.com/ggml-model-whisper-base.en.bin',
};
let sizes = {
@ -450,22 +281,33 @@
let url = urls[model];
let dst = 'whisper.bin';
let el = document.getElementById('fetch-whisper-progress');
let size_mb = sizes[model];
model_whisper = model;
document.getElementById('fetch-whisper-tiny-en').style.display = 'none';
document.getElementById('fetch-whisper-base-en').style.display = 'none';
document.getElementById('model-whisper-status').innerHTML = 'Whisper model: loading "' + model + '" ... ';
document.getElementById('model-whisper-status').innerHTML = 'loading "' + model + '" ... ';
cbProgress = function(p) {
let el = document.getElementById('fetch-whisper-progress');
el.innerHTML = Math.round(100*p) + '%';
};
cbCancel = function() {
var el;
el = document.getElementById('fetch-whisper-tiny-en'); if (el) el.style.display = 'inline-block';
el = document.getElementById('fetch-whisper-base-en'); if (el) el.style.display = 'inline-block';
el = document.getElementById('model-whisper-status'); if (el) el.innerHTML = '';
};
loadRemote(url, dst, el, size_mb);
loadRemote(url, dst, size_mb, cbProgress, storeFS, cbCancel, printTextarea);
}
function loadGPT2(model) {
let urls = {
'small': 'https://talk.ggerganov.com/ggml-model-gpt-2-117M.bin',
'medium': 'https://talk.ggerganov.com/ggml-model-gpt-2-345M.bin',
'small': 'https://whisper.ggerganov.com/ggml-model-gpt-2-117M.bin',
'medium': 'https://whisper.ggerganov.com/ggml-model-gpt-2-345M.bin',
};
let sizes = {
@ -475,15 +317,25 @@
let url = urls[model];
let dst = 'gpt-2.bin';
let el = document.getElementById('fetch-gpt-2-progress');
let size_mb = sizes[model];
model_gpt_2 = model;
document.getElementById('fetch-gpt-2-small').style.display = 'none';
document.getElementById('model-gpt-2-status').innerHTML = 'GPT-2 model: loading "' + model + '" ... ';
document.getElementById('model-gpt-2-status').innerHTML = 'loading "' + model + '" ... ';
cbProgress = function(p) {
let el = document.getElementById('fetch-gpt-2-progress');
el.innerHTML = Math.round(100*p) + '%';
};
loadRemote(url, dst, el, size_mb);
cbCancel = function() {
var el;
el = document.getElementById('fetch-gpt-2-small') ; if (el) el.style.display = 'inline-block';
el = document.getElementById('model-gpt-2-status'); if (el) el.innerHTML = '';
};
loadRemote(url, dst, size_mb, cbProgress, storeFS, cbCancel, printTextarea);
}
//
@ -507,7 +359,7 @@
context = new AudioContext({
sampleRate: 16000,
channelCount: 1,
echoCancellation: true,
echoCancellation: false,
autoGainControl: true,
noiseSuppression: true,
});
@ -652,12 +504,6 @@
Module.force_speak(instance);
}
async function clearCache() {
if (confirm('Are you sure you want to clear the cache?\nAll the models will be downloaded again.')) {
indexedDB.deleteDatabase(dbName);
}
}
//
// main
//

@ -164,7 +164,7 @@ void AudioInputCallback(void * inUserData,
params.print_realtime = true;
params.print_progress = false;
params.print_timestamps = true;
params.print_special_tokens = false;
params.print_special = false;
params.translate = false;
params.language = "en";
params.n_threads = 4;

@ -1,4 +1,5 @@
set(TARGET whisper.wasm)
configure_file(${CMAKE_CURRENT_SOURCE_DIR}/index-tmpl.html ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/${TARGET}/index.html @ONLY)
configure_file(${CMAKE_CURRENT_SOURCE_DIR}/../helpers.js ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/${TARGET}/helpers.js @ONLY)
configure_file(${CMAKE_SOURCE_DIR}/bindings/javascript/whisper.js ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/${TARGET}/whisper.js COPYONLY)

@ -26,10 +26,9 @@ Link: https://whisper.ggerganov.com
![image](https://user-images.githubusercontent.com/1991296/197348344-1a7fead8-3dae-4922-8b06-df223a206603.png)
## Build instructions
```bash
```bash (v3.1.2)
# build using Emscripten
git clone https://github.com/ggerganov/whisper.cpp
cd whisper.cpp
@ -38,6 +37,6 @@ emcmake cmake ..
make -j
# copy the produced page to your HTTP path
cp bin/whisper.wasm/index.html /path/to/html/
cp bin/whisper.wasm/whisper.js /path/to/html/
cp bin/whisper.wasm/* /path/to/html/
cp bin/libwhisper.worker.js /path/to/html/
```

@ -45,13 +45,14 @@
<br><br><hr>
<div id="model">
Model:
Whisper model: <span id="model-whisper-status"></span>
<button id="fetch-whisper-tiny-en" onclick="loadWhisper('tiny.en')">tiny.en (75 MB)</button>
<button id="fetch-whisper-tiny" onclick="loadWhisper('tiny')">tiny (75 MB)</button>
<button id="fetch-whisper-base-en" onclick="loadWhisper('base.en')">base.en (142 MB)</button>
<button id="fetch-whisper-base" onclick="loadWhisper('base')">base (142 MB)</button>
<span id="fetch-whisper-progress"></span>
<input type="file" id="file" name="file" onchange="loadFile(event, 'whisper.bin')" />
<input type="file" id="whisper-file" name="file" onchange="loadFile(event, 'whisper.bin')" />
</div>
<br>
@ -185,6 +186,7 @@
</div>
</div>
<script type="text/javascript" src="helpers.js"></script>
<script type='text/javascript'>
// TODO: convert audio buffer to WAV
function setAudio(audio) {
@ -204,28 +206,15 @@
function changeInput(input) {
if (input == 'file') {
document.getElementById('input_file').style.display = 'block';
document.getElementById('input_mic').style.display = 'none';
document.getElementById('progress').style.display = 'none';
document.getElementById('input_mic' ).style.display = 'none';
document.getElementById('progress' ).style.display = 'none';
} else {
document.getElementById('input_file').style.display = 'none';
document.getElementById('input_mic').style.display = 'block';
document.getElementById('progress').style.display = 'block';
document.getElementById('input_mic' ).style.display = 'block';
document.getElementById('progress' ).style.display = 'block';
}
}
var printTextarea = (function() {
var element = document.getElementById('output');
if (element) element.alue = ''; // clear browser cache
return function(text) {
if (arguments.length > 1) text = Array.prototype.slice.call(arguments).join(' ');
console.log(text);
if (element) {
element.value += text + "\n";
element.scrollTop = element.scrollHeight; // focus on bottom
}
};
})();
var Module = {
print: printTextarea,
printErr: printTextarea,
@ -250,7 +239,7 @@
// the whisper instance
var instance = null;
var model_fname = '';
var model_whisper = '';
// helper function
function convertTypedArray(src, type) {
@ -278,8 +267,11 @@
Module.FS_createDataFile("/", fname, buf, true, true);
model_fname = fname;
printTextarea('js: stored model: ' + fname + ' size: ' + buf.length);
model_whisper = fname;
document.getElementById('model-whisper-status').innerHTML = 'loaded "' + model_whisper + '"!';
printTextarea('storeFS: stored model: ' + fname + ' size: ' + buf.length);
}
function loadFile(event, fname) {
@ -288,8 +280,8 @@
return;
}
printTextarea("js: loading model: " + file.name + ", size: " + file.size + " bytes");
printTextarea('js: please wait ...');
printTextarea("loadFile: loading model: " + file.name + ", size: " + file.size + " bytes");
printTextarea('loadFile: please wait ...');
var reader = new FileReader();
reader.onload = function(event) {
@ -300,160 +292,10 @@
document.getElementById('fetch-whisper-tiny-en').style.display = 'none';
document.getElementById('fetch-whisper-base-en').style.display = 'none';
document.getElementById('fetch-whisper-tiny').style.display = 'none';
document.getElementById('fetch-whisper-base').style.display = 'none';
}
// fetch a remote file from remote URL using the Fetch API
async function fetchRemote(url, elProgress) {
printTextarea('js: downloading with fetch()...');
const response = await fetch(
url,
{
method: 'GET',
headers: {
'Content-Type': 'application/octet-stream',
},
}
);
if (!response.ok) {
printTextarea('js: failed to fetch ' + url);
return;
}
const contentLength = response.headers.get('content-length');
const total = parseInt(contentLength, 10);
const reader = response.body.getReader();
var chunks = [];
var receivedLength = 0;
var progressLast = -1;
while (true) {
const { done, value } = await reader.read();
if (done) {
break;
}
chunks.push(value);
receivedLength += value.length;
if (contentLength) {
// update progress bar element with the new percentage
elProgress.innerHTML = Math.round((receivedLength / total) * 100) + '%';
var progressCur = Math.round((receivedLength / total) * 10);
if (progressCur != progressLast) {
printTextarea('js: fetching ' + 10*progressCur + '% ...');
progressLast = progressCur;
}
}
}
var chunksAll = new Uint8Array(receivedLength);
var position = 0;
for (var chunk of chunks) {
chunksAll.set(chunk, position);
position += chunk.length;
}
return chunksAll;
}
// load remote data
// - check if the data is already in the IndexedDB
// - if not, fetch it from the remote URL and store it in the IndexedDB
// - store it in WASM memory
function loadRemote(url, dst, elProgress, size_mb) {
// query the storage quota and print it
navigator.storage.estimate().then(function (estimate) {
printTextarea('js: storage quota: ' + estimate.quota + ' bytes');
printTextarea('js: storage usage: ' + estimate.usage + ' bytes');
});
// check if the data is already in the IndexedDB
var request = indexedDB.open(dbName, dbVersion);
request.onupgradeneeded = function (event) {
var db = event.target.result;
if (db.version == 1) {
var objectStore = db.createObjectStore('models', { autoIncrement: false });
printTextarea('js: created IndexedDB ' + db.name + ' version ' + db.version);
} else {
// clear the database
var objectStore = event.currentTarget.transaction.objectStore('models');
objectStore.clear();
printTextarea('js: cleared IndexedDB ' + db.name + ' version ' + db.version);
}
};
request.onsuccess = function (event) {
var db = event.target.result;
var transaction = db.transaction(['models'], 'readonly');
var objectStore = transaction.objectStore('models');
var request = objectStore.get(url);
request.onsuccess = function (event) {
if (request.result) {
printTextarea('js: "' + url + '" is already in the IndexedDB');
storeFS(dst, request.result);
} else {
// data is not in the IndexedDB
printTextarea('js: "' + url + '" is not in the IndexedDB');
// alert and ask the user to confirm
if (!confirm('You are about to download ' + size_mb + ' MB of data.\nThe model data will be cached in the browser for future use.\n\nPress OK to continue.')) {
var el;
el = document.getElementById('fetch-whisper-tiny-en'); if (el) el.style.display = 'inline-block';
el = document.getElementById('fetch-whisper-tiny'); if (el) el.style.display = 'inline-block';
el = document.getElementById('fetch-whisper-base-en'); if (el) el.style.display = 'inline-block';
el = document.getElementById('fetch-whisper-base'); if (el) el.style.display = 'inline-block';
return;
}
fetchRemote(url, elProgress).then(function (data) {
if (data) {
// store the data in the IndexedDB
var request = indexedDB.open(dbName, dbVersion);
request.onsuccess = function (event) {
var db = event.target.result;
var transaction = db.transaction(['models'], 'readwrite');
var objectStore = transaction.objectStore('models');
var request = objectStore.put(data, url);
request.onsuccess = function (event) {
printTextarea('js: "' + url + '" stored in the IndexedDB');
storeFS(dst, data);
};
request.onerror = function (event) {
printTextarea('js: failed to store "' + url + '" in the IndexedDB');
};
};
}
});
}
};
request.onerror = function (event) {
printTextarea('js: failed to get data from the IndexedDB');
};
};
request.onerror = function (event) {
printTextarea('js: failed to open IndexedDB');
};
request.onblocked = function (event) {
printTextarea('js: failed to open IndexedDB: blocked');
};
request.onabort = function (event) {
printTextarea('js: failed to open IndexedDB: abort');
};
document.getElementById('fetch-whisper-tiny' ).style.display = 'none';
document.getElementById('fetch-whisper-base' ).style.display = 'none';
document.getElementById('whisper-file' ).style.display = 'none';
document.getElementById('model-whisper-status' ).innerHTML = 'loaded model: ' + file.name;
}
function loadWhisper(model) {
@ -473,17 +315,33 @@
let url = urls[model];
let dst = 'whisper.bin';
let el = document.getElementById('fetch-whisper-progress');
let size_mb = sizes[model];
model_whisper = model;
document.getElementById('fetch-whisper-tiny-en').style.display = 'none';
document.getElementById('fetch-whisper-base-en').style.display = 'none';
document.getElementById('fetch-whisper-tiny').style.display = 'none';
document.getElementById('fetch-whisper-base').style.display = 'none';
document.getElementById('fetch-whisper-tiny' ).style.display = 'none';
document.getElementById('fetch-whisper-base' ).style.display = 'none';
document.getElementById('whisper-file' ).style.display = 'none';
document.getElementById('model-whisper-status' ).innerHTML = 'loading model: ' + model;
cbProgress = function(p) {
let el = document.getElementById('fetch-whisper-progress');
el.innerHTML = Math.round(100*p) + '%';
};
cbCancel = function() {
var el;
el = document.getElementById('fetch-whisper-tiny-en'); if (el) el.style.display = 'inline-block';
el = document.getElementById('fetch-whisper-base-en'); if (el) el.style.display = 'inline-block';
el = document.getElementById('fetch-whisper-tiny' ); if (el) el.style.display = 'inline-block';
el = document.getElementById('fetch-whisper-base' ); if (el) el.style.display = 'inline-block';
el = document.getElementById('whisper-file' ); if (el) el.style.display = 'inline-block';
el = document.getElementById('model-whisper-status' ); if (el) el.innerHTML = '';
};
loadRemote(url, dst, el, size_mb);
loadRemote(url, dst, size_mb, cbProgress, storeFS, cbCancel, printTextarea);
}
//
@ -651,7 +509,7 @@
if (instance) {
printTextarea("js: whisper initialized, instance: " + instance);
document.getElementById('model').innerHTML = 'Model loaded: ' + model_fname;
document.getElementById('model').innerHTML = 'Model loaded: ' + model_whisper;
}
}
@ -668,7 +526,6 @@
if (instance) {
printTextarea('');
printTextarea('js: processing - this might take a while ...');
printTextarea('js: the page will be unresponsive until the processing is completed');
printTextarea('');
setTimeout(function() {

@ -41,5 +41,24 @@ https://huggingface.co/datasets/ggerganov/whisper.cpp/tree/main
## Model files for testing purposes
The model files pefixed with `for-tests-` are empty (i.e. do not contain any weights) and are used by the CI for testing purposes.
They are directly included in this repository for convenience and the Github Actions CI uses them to run various sanitizer tests.
The model files prefixed with `for-tests-` are empty (i.e. do not contain any weights) and are used by the CI for
testing purposes. They are directly included in this repository for convenience and the Github Actions CI uses them to
run various sanitizer tests.
## Fine-tuned models
There are community efforts for creating fine-tuned Whisper models using extra training data. For example, this
[blog post](https://huggingface.co/blog/fine-tune-whisper) describes a method for fine-tuning using Hugging Face (HF)
Transformer implementation of Whisper. The produced models are in slightly different format compared to the original
OpenAI format. To read the HF models you can use the [convert-h5-to-ggml.py](convert-h5-to-ggml.py) script like this:
```bash
git clone https://github.com/openai/whisper
git clone https://github.com/ggerganov/whisper.cpp
# clone HF fine-tuned model (this is just an example)
git clone https://huggingface.co/openai/whisper-base.en
# convert the model to ggml
python3 ./whisper.cpp/models/convert-h5-to-ggml.py ./whisper-medium/ ./whisper .
```

@ -518,15 +518,6 @@ static bool whisper_model_load(const std::string & fname, whisper_context & wctx
wctx.buf_memory.resize(MEM_REQ_MEMORY.at(model.type));
wctx.buf_compute.resize(std::max(MEM_REQ_ENCODE.at(model.type), MEM_REQ_DECODE.at(model.type)));
wctx.buf_compute_layer.resize(std::max(MEM_REQ_ENCODE_LAYER.at(model.type), MEM_REQ_DECODE_LAYER.at(model.type)));
// this is the total memory required to run the inference
const size_t mem_required =
wctx.buf_model->size() +
wctx.buf_memory.size() +
wctx.buf_compute.size() +
wctx.buf_compute_layer.size();
fprintf(stderr, "%s: mem_required = %.2f MB\n", __func__, mem_required / 1024.0 / 1024.0);
}
// load mel filters
@ -599,11 +590,21 @@ static bool whisper_model_load(const std::string & fname, whisper_context & wctx
}
}
{
// this is the total memory required to run the inference
const size_t mem_required =
wctx.buf_model->size() +
wctx.buf_memory.size() +
wctx.buf_compute.size() +
wctx.buf_compute_layer.size();
fprintf(stderr, "%s: mem_required = %7.2f MB\n", __func__, mem_required / 1024.0 / 1024.0);
}
// for the big tensors, we have the option to store the data in 16-bit floats
// in order to save memory and also to speed up the computation
const ggml_type wtype = model.hparams.f16 ? GGML_TYPE_F16 : GGML_TYPE_F32;
size_t ctx_size = 0;
size_t ctx_mem_size = 0;
@ -722,7 +723,7 @@ static bool whisper_model_load(const std::string & fname, whisper_context & wctx
ctx_size += (15 + 15*n_audio_layer + 24*n_text_layer)*256; // object overhead
fprintf(stderr, "%s: ggml ctx size = %6.2f MB\n", __func__, ctx_size/(1024.0*1024.0));
fprintf(stderr, "%s: ggml ctx size = %7.2f MB\n", __func__, ctx_size/(1024.0*1024.0));
}
// create the ggml context
@ -983,7 +984,7 @@ static bool whisper_model_load(const std::string & fname, whisper_context & wctx
ggml_nbytes(model.memory_k) + ggml_nbytes(model.memory_v) +
ggml_nbytes(model.memory_cross_k) + ggml_nbytes(model.memory_cross_v);
fprintf(stderr, "%s: memory size = %8.2f MB\n", __func__, memory_size/1024.0/1024.0);
fprintf(stderr, "%s: memory size = %7.2f MB\n", __func__, memory_size/1024.0/1024.0);
}
// load weights
@ -1047,7 +1048,7 @@ static bool whisper_model_load(const std::string & fname, whisper_context & wctx
model.n_loaded++;
}
fprintf(stderr, "%s: model size = %8.2f MB\n", __func__, total_size/1024.0/1024.0);
fprintf(stderr, "%s: model size = %7.2f MB\n", __func__, total_size/1024.0/1024.0);
if (model.n_loaded == 0) {
fprintf(stderr, "%s: WARN no tensors loaded from model file - assuming empty model for testing\n", __func__);
@ -2379,6 +2380,12 @@ void whisper_print_timings(struct whisper_context * ctx) {
fprintf(stderr, "%s: total time = %8.2f ms\n", __func__, (t_end_us - ctx->t_start_us)/1000.0f);
}
void whisper_reset_timings(struct whisper_context * ctx) {
ctx->t_sample_us = 0;
ctx->t_encode_us = 0;
ctx->t_decode_us = 0;
}
////////////////////////////////////////////////////////////////////////////
struct whisper_full_params whisper_full_default_params(enum whisper_sampling_strategy strategy) {
@ -2398,7 +2405,7 @@ struct whisper_full_params whisper_full_default_params(enum whisper_sampling_str
/*.translate =*/ false,
/*.no_context =*/ false,
/*.single_segment =*/ false,
/*.print_special_tokens =*/ false,
/*.print_special =*/ false,
/*.print_progress =*/ true,
/*.print_realtime =*/ false,
/*.print_timestamps =*/ true,
@ -2444,7 +2451,7 @@ struct whisper_full_params whisper_full_default_params(enum whisper_sampling_str
/*.translate =*/ false,
/*.no_context =*/ false,
/*.single_segment =*/ false,
/*.print_special_tokens =*/ false,
/*.print_special =*/ false,
/*.print_progress =*/ true,
/*.print_realtime =*/ false,
/*.print_timestamps =*/ true,
@ -2761,7 +2768,7 @@ int whisper_full(
// ctx->vocab.id_to_token[tokens_cur[i].id].c_str(), tokens_cur[i].p,
// ctx->vocab.id_to_token[tokens_cur[i].tid].c_str(), tokens_cur[i].pt);
if (params.print_special_tokens == false && tokens_cur[i].id >= whisper_token_eot(ctx)) {
if (params.print_special == false && tokens_cur[i].id >= whisper_token_eot(ctx)) {
} else {
text += whisper_token_to_str(ctx, tokens_cur[i].id);
}

@ -167,6 +167,7 @@ extern "C" {
// Performance information
WHISPER_API void whisper_print_timings(struct whisper_context * ctx);
WHISPER_API void whisper_reset_timings(struct whisper_context * ctx);
////////////////////////////////////////////////////////////////////////////
@ -192,7 +193,7 @@ extern "C" {
bool translate;
bool no_context;
bool single_segment; // force single segment output (useful for streaming)
bool print_special_tokens;
bool print_special;
bool print_progress;
bool print_realtime;
bool print_timestamps;

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