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whisper.cpp
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Extend C-style API with full inference methods

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pull/23/head
Georgi Gerganov 2 years ago
parent 6b77124e01
commit eba33adadd
4 changed files with 328 additions and 348 deletions
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182
main.cpp
Unescape View File

@ -5,17 +5,11 @@
#define DR_WAV_IMPLEMENTATION
#include "dr_wav.h"
#include <cassert>
#include <cstdio>
#include <string>
#include <thread>
#include <vector>
int64_t get_time_us() {
return std::chrono::duration_cast<std::chrono::microseconds>(
std::chrono::high_resolution_clock::now().time_since_epoch()).count();
}
// 500 -> 00:05.000
// 6000 -> 01:00.000
std::string to_timestamp(int64_t t) {
@ -30,11 +24,6 @@ std::string to_timestamp(int64_t t) {
return std::string(buf);
}
struct whisper_result {
whisper_token id;
int64_t t;
};
// command-line parameters
struct whisper_params {
int32_t seed = -1; // RNG seed, not used currently
@ -111,8 +100,6 @@ void whisper_print_usage(int argc, char ** argv, const whisper_params & params)
}
int main(int argc, char ** argv) {
const int64_t t_main_start_us = get_time_us();
whisper_params params;
if (whisper_params_parse(argc, argv, params) == false) {
@ -142,7 +129,7 @@ int main(int argc, char ** argv) {
return 3;
}
if (wav.sampleRate != SAMPLE_RATE) {
if (wav.sampleRate != WHISPER_SAMPLE_RATE) {
fprintf(stderr, "%s: WAV file '%s' must be 16 kHz\n", argv[0], params.fname_inp.c_str());
return 4;
}
@ -172,12 +159,6 @@ int main(int argc, char ** argv) {
}
}
// compute log mel spectrogram
if (whisper_pcm_to_mel(ctx, pcmf32.data(), pcmf32.size(), params.n_threads) != 0) {
fprintf(stderr, "%s: failed to compute log mel spectrogram\n", argv[0]);
return 6;
}
// print some info about the processing
{
printf("\n");
@ -189,168 +170,43 @@ int main(int argc, char ** argv) {
}
}
printf("%s: processing %d samples (%.1f sec), %d threads, lang = %s, task = %s, timestamps = %d ...\n",
__func__, int(pcmf32.size()), float(pcmf32.size())/SAMPLE_RATE, params.n_threads,
__func__, int(pcmf32.size()), float(pcmf32.size())/WHISPER_SAMPLE_RATE, params.n_threads,
params.language.c_str(),
params.translate ? "translate" : "transcribe",
params.no_timestamps ? 0 : 1);
printf("\n");
}
// the accumulated text context so far
std::vector<whisper_token> prompt_past = { };
// these tokens determine the task that will be performed
std::vector<whisper_token> prompt_init = { whisper_token_sot(ctx) };
if (whisper_is_multilingual(ctx)) {
prompt_init.push_back(whisper_token_sot(ctx) + 1 + whisper_lang_id(params.language.c_str()));
if (params.translate) {
prompt_init.push_back(whisper_token_translate());
} else {
prompt_init.push_back(whisper_token_transcribe());
}
}
// the generated text including timestamps
//std::vector<whisper_result> result_all;
// main loop
int seek = 0;
while (true) {
if (seek >= whisper_n_len(ctx)) {
break;
}
// encode audio features starting at offset seek
if (whisper_encode(ctx, seek, params.n_threads) != 0) {
fprintf(stderr, "%s: failed to encode\n", __func__);
return 7;
}
std::vector<whisper_token> prompt;
int n_past = 0;
// if we have already generated some text, use it as a prompt to condition the next generation
if (prompt_past.size() > 0) {
int n_take = std::min(whisper_n_text_ctx(ctx)/2, int(prompt_past.size()));
prompt = { whisper_token_prev(ctx) };
prompt.insert(prompt.begin() + 1, prompt_past.end() - n_take, prompt_past.end());
prompt_past.clear();
prompt_past.insert(prompt_past.end(), prompt.begin() + 1, prompt.end());
}
prompt.insert(prompt.end(), prompt_init.begin(), prompt_init.end());
bool done = false;
int seek_delta = 100*CHUNK_SIZE;
whisper_token last_id = 0;
// print the prompt
//printf("\n\n");
//for (int i = 0; i < prompt.size(); i++) {
// printf("%s: prompt[%d] = %s\n", __func__, i, vocab.id_to_token[prompt[i]].c_str());
//}
//printf("\n\n");
// the accumulated transcription in the current interation
int result_len = 0;
std::vector<whisper_result> result_cur;
for (int i = 0; i < whisper_n_text_ctx(ctx)/2 - 4; ++i) {
if (whisper_decode(ctx, prompt.data(), prompt.size(), n_past, params.n_threads) != 0) {
fprintf(stderr, "%s: failed to decode\n", __func__);
return 8;
}
n_past += prompt.size();
prompt.clear();
// very basic greedy sampling strategy:
//
// - always take the most probable token
//
// more sophisticated sampling strategies could be implemented here, but we keep it simple
// feel free to experiment!
//
// run the inference
{
const int n_vocab = whisper_n_vocab(ctx);
whisper_token id = 0;
whisper_token tid = whisper_token_beg(ctx);
id = whisper_sample_best(ctx, result_len == 0);
if (i > 0) {
tid = whisper_sample_timestamp(ctx);
}
// update sliding window
if (id > whisper_token_beg(ctx)) {
seek_delta = 2*(id - whisper_token_beg(ctx));
result_len = i + 1;
}
last_id = id;
// add it to the context
prompt.push_back(id);
result_cur.push_back({ id, seek + 2*(tid - whisper_token_beg(ctx)) });
whisper_full_params wparams = whisper_full_default_params(WHISPER_DECODE_GREEDY);
//printf("%s: %s\n", __func__, vocab.id_to_token[id].c_str());
wparams.print_special_tokens = params.print_special_tokens;
// end of text token
if (id == whisper_token_eot(ctx)) {
break;
}
}
if (done) {
break;
}
if (whisper_full(ctx, wparams, pcmf32.data(), pcmf32.size()) != 0) {
fprintf(stderr, "%s: failed to process audio\n", argv[0]);
return 6;
}
result_cur.resize(result_len);
//result_all.insert(result_all.end(), result_cur.begin(), result_cur.end());
for (const auto & r : result_cur) {
prompt_past.push_back(r.id);
}
// print result;
{
printf("\n");
// print the text from this iteration
if (result_cur.size() > 0) {
auto t0 = result_cur.front().t;
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);
std::string text = "";
for (int i = 0; i < result_cur.size(); i++) {
if (params.print_special_tokens == false && result_cur[i].id >= whisper_token_eot(ctx)) {
} else {
text += whisper_token_to_str(ctx, result_cur[i].id);
}
if (result_cur[i].id > whisper_token_beg(ctx)) {
const auto t1 = result_cur[i].t;
if (!text.empty()) {
if (params.no_timestamps) {
printf ("%s", text.c_str());
printf ("%s", text);
fflush(stdout);
} else {
printf ("[%s --> %s] %s\n", to_timestamp(t0).c_str(), to_timestamp(t1).c_str(), text.c_str());
}
}
text = "";
while (result_cur[i].id > whisper_token_beg(ctx) && i < result_cur.size()) {
i++;
}
i--;
t0 = result_cur[i].t;
}
}
const int64_t t0 = whisper_full_get_segment_t0(ctx, i);
const int64_t t1 = whisper_full_get_segment_t1(ctx, i);
if (!text.empty()) {
printf ("[%s --> %s] %s\n", to_timestamp(t0).c_str(), to_timestamp(seek + seek_delta).c_str(), text.c_str());
printf ("[%s --> %s] %s\n", to_timestamp(t0).c_str(), to_timestamp(t1).c_str(), text);
}
}
}
seek += seek_delta;
}
whisper_print_timings(ctx);

186
stream.cpp
Unescape View File

@ -18,11 +18,6 @@
#include <thread>
#include <vector>
int64_t get_time_us() {
return std::chrono::duration_cast<std::chrono::microseconds>(
std::chrono::high_resolution_clock::now().time_since_epoch()).count();
}
// 500 -> 00:05.000
// 6000 -> 01:00.000
std::string to_timestamp(int64_t t) {
@ -37,11 +32,6 @@ std::string to_timestamp(int64_t t) {
return std::string(buf);
}
struct whisper_result {
whisper_token id;
int64_t t;
};
// command-line parameters
struct whisper_params {
int32_t seed = -1; // RNG seed, not used currently
@ -155,7 +145,7 @@ bool audio_sdl_init(const int capture_id) {
SDL_zero(capture_spec_requested);
SDL_zero(capture_spec_obtained);
capture_spec_requested.freq = SAMPLE_RATE;
capture_spec_requested.freq = WHISPER_SAMPLE_RATE;
capture_spec_requested.format = AUDIO_F32;
capture_spec_requested.channels = 1;
capture_spec_requested.samples = 1024;
@ -186,8 +176,6 @@ bool audio_sdl_init(const int capture_id) {
///////////////////////////
int main(int argc, char ** argv) {
const int64_t t_main_start_us = get_time_us();
whisper_params params;
if (whisper_params_parse(argc, argv, params) == false) {
@ -209,7 +197,7 @@ int main(int argc, char ** argv) {
struct whisper_context * ctx = whisper_init(params.model.c_str());
const int n_samples_30s = 30*SAMPLE_RATE;
const int n_samples_30s = 30*WHISPER_SAMPLE_RATE;
std::vector<float> pcmf32(n_samples_30s, 0.0f);
std::vector<float> pcmf32_old;
@ -224,7 +212,7 @@ int main(int argc, char ** argv) {
}
}
printf("%s: processing %d samples (%.1f sec), %d threads, lang = %s, task = %s, timestamps = %d ...\n",
__func__, int(pcmf32.size()), float(pcmf32.size())/SAMPLE_RATE, params.n_threads,
__func__, int(pcmf32.size()), float(pcmf32.size())/WHISPER_SAMPLE_RATE, params.n_threads,
params.language.c_str(),
params.translate ? "translate" : "transcribe",
params.no_timestamps ? 0 : 1);
@ -250,7 +238,7 @@ int main(int argc, char ** argv) {
}
// process 3 seconds of new audio
while ((int) SDL_GetQueuedAudioSize(g_dev_id_in) < 3*SAMPLE_RATE*sizeof(float)) {
while ((int) SDL_GetQueuedAudioSize(g_dev_id_in) < 3*WHISPER_SAMPLE_RATE*sizeof(float)) {
SDL_Delay(1);
}
const int n_samples_new = SDL_GetQueuedAudioSize(g_dev_id_in)/sizeof(float);
@ -271,167 +259,37 @@ int main(int argc, char ** argv) {
pcmf32_old = pcmf32;
// compute log mel spectrogram
if (whisper_pcm_to_mel(ctx, pcmf32.data(), pcmf32.size(), params.n_threads) != 0) {
fprintf(stderr, "%s: failed to compute log mel spectrogram\n", argv[0]);
return 6;
}
// the accumulated text context so far
std::vector<whisper_token> prompt_past = { };
// these tokens determine the task that will be performed
std::vector<whisper_token> prompt_init = { whisper_token_sot(ctx) };
if (whisper_is_multilingual(ctx)) {
prompt_init.push_back(whisper_token_sot(ctx) + 1 + whisper_lang_id(params.language.c_str()));
if (params.translate) {
prompt_init.push_back(whisper_token_translate());
} else {
prompt_init.push_back(whisper_token_transcribe());
}
}
// the generated text including timestamps
//std::vector<whisper_result> result_all;
// main loop
int seek = 0;
while (true) {
if (seek >= whisper_n_len(ctx)) {
break;
}
// encode audio features starting at offset seek
if (whisper_encode(ctx, seek, params.n_threads) != 0) {
fprintf(stderr, "%s: failed to encode\n", __func__);
return 7;
}
std::vector<whisper_token> prompt;
int n_past = 0;
// if we have already generated some text, use it as a prompt to condition the next generation
if (prompt_past.size() > 0) {
int n_take = std::min(whisper_n_text_ctx(ctx)/2, int(prompt_past.size()));
prompt = { whisper_token_prev(ctx) };
prompt.insert(prompt.begin() + 1, prompt_past.end() - n_take, prompt_past.end());
prompt_past.clear();
prompt_past.insert(prompt_past.end(), prompt.begin() + 1, prompt.end());
}
prompt.insert(prompt.end(), prompt_init.begin(), prompt_init.end());
bool done = false;
int seek_delta = 100*CHUNK_SIZE;
whisper_token last_id = 0;
// print the prompt
//printf("\n\n");
//for (int i = 0; i < prompt.size(); i++) {
// printf("%s: prompt[%d] = %s\n", __func__, i, vocab.id_to_token[prompt[i]].c_str());
//}
//printf("\n\n");
// the accumulated transcription in the current interation
int result_len = 0;
std::vector<whisper_result> result_cur;
for (int i = 0; i < whisper_n_text_ctx(ctx)/2 - 4; ++i) {
if (whisper_decode(ctx, prompt.data(), prompt.size(), n_past, params.n_threads) != 0) {
fprintf(stderr, "%s: failed to decode\n", __func__);
return 8;
}
n_past += prompt.size();
prompt.clear();
// very basic greedy sampling strategy:
//
// - always take the most probable token
//
// more sophisticated sampling strategies could be implemented here, but we keep it simple
// feel free to experiment!
//
// run the inference
{
const int n_vocab = whisper_n_vocab(ctx);
whisper_full_params wparams = whisper_full_default_params(WHISPER_DECODE_GREEDY);
whisper_token id = 0;
whisper_token tid = whisper_token_beg(ctx);
id = whisper_sample_best(ctx, result_len == 0);
if (i > 0) {
tid = whisper_sample_timestamp(ctx);
}
// update sliding window
if (id > whisper_token_beg(ctx)) {
seek_delta = 2*(id - whisper_token_beg(ctx));
result_len = i + 1;
}
last_id = id;
wparams.print_progress = false;
wparams.print_special_tokens = params.print_special_tokens;
// add it to the context
prompt.push_back(id);
result_cur.push_back({ id, seek + 2*(tid - whisper_token_beg(ctx)) });
//printf("%s: %s\n", __func__, vocab.id_to_token[id].c_str());
// end of text token
if (id == whisper_token_eot(ctx)) {
break;
}
}
if (done) {
break;
}
if (whisper_full(ctx, wparams, pcmf32.data(), pcmf32.size()) != 0) {
fprintf(stderr, "%s: failed to process audio\n", argv[0]);
return 6;
}
result_cur.resize(result_len);
//result_all.insert(result_all.end(), result_cur.begin(), result_cur.end());
for (const auto & r : result_cur) {
prompt_past.push_back(r.id);
}
// print result;
{
printf("\n");
// print the text from this iteration
if (result_cur.size() > 0) {
auto t0 = result_cur.front().t;
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);
std::string text = "";
for (int i = 0; i < result_cur.size(); i++) {
if (params.print_special_tokens == false && result_cur[i].id >= whisper_token_eot(ctx)) {
} else {
text += whisper_token_to_str(ctx, result_cur[i].id);
}
if (result_cur[i].id > whisper_token_beg(ctx)) {
const auto t1 = result_cur[i].t;
if (!text.empty()) {
if (params.no_timestamps) {
printf ("%s", text.c_str());
printf ("%s", text);
fflush(stdout);
} else {
printf ("[%s --> %s] %s\n", to_timestamp(t0).c_str(), to_timestamp(t1).c_str(), text.c_str());
}
}
text = "";
while (result_cur[i].id > whisper_token_beg(ctx) && i < result_cur.size()) {
i++;
}
i--;
t0 = result_cur[i].t;
}
}
const int64_t t0 = whisper_full_get_segment_t0(ctx, i);
const int64_t t1 = whisper_full_get_segment_t1(ctx, i);
if (!text.empty()) {
printf ("[%s --> %s] %s\n", to_timestamp(t0).c_str(), to_timestamp(seek + seek_delta).c_str(), text.c_str());
printf ("[%s --> %s] %s\n", to_timestamp(t0).c_str(), to_timestamp(t1).c_str(), text);
}
}
}
seek += seek_delta;
}
}

266
whisper.cpp
Unescape View File

@ -210,8 +210,15 @@ struct whisper_vocab {
};
struct whisper_result {
whisper_vocab::id id;
int64_t t;
whisper_token id;
};
struct whisper_segment {
int64_t t0;
int64_t t1;
std::string text;
};
// medium
@ -395,6 +402,9 @@ struct whisper_context {
std::vector<float> probs;
std::vector<float> logits;
std::vector<whisper_result> result_cur;
std::vector<whisper_segment> result_all;
};
// load the model from a ggml file
@ -1946,8 +1956,8 @@ bool log_mel_spectrogram(
const int n_fft = 1 + fft_size/2;
printf("%s: n_samples = %d, n_len = %d\n", __func__, n_samples, mel.n_len);
printf("%s: recording length: %f s\n", __func__, (float) n_samples/sample_rate);
//printf("%s: n_samples = %d, n_len = %d\n", __func__, n_samples, mel.n_len);
//printf("%s: recording length: %f s\n", __func__, (float) n_samples/sample_rate);
std::vector<std::thread> workers(n_threads);
for (int iw = 0; iw < n_threads; ++iw) {
@ -2066,7 +2076,7 @@ void whisper_free(struct whisper_context * ctx) {
int whisper_pcm_to_mel(struct whisper_context * ctx, const float * samples, int n_samples, int n_threads) {
const int64_t t_start_us = ggml_time_us();
if (!log_mel_spectrogram(samples, n_samples, SAMPLE_RATE, N_FFT, HOP_LENGTH, N_MEL, n_threads, ctx->model.filters, ctx->mel)) {
if (!log_mel_spectrogram(samples, n_samples, WHISPER_SAMPLE_RATE, WHISPER_N_FFT, WHISPER_HOP_LENGTH, WHISPER_N_MEL, n_threads, ctx->model.filters, ctx->mel)) {
fprintf(stderr, "%s: failed to compute mel spectrogram\n", __func__);
return -1;
}
@ -2081,8 +2091,8 @@ int whisper_set_mel(
const float * data,
int n_len,
int n_mel) {
if (n_mel != N_MEL) {
fprintf(stderr, "%s: invalid number of mel bands: %d (expected %d)\n", __func__, n_mel, N_MEL);
if (n_mel != WHISPER_N_MEL) {
fprintf(stderr, "%s: invalid number of mel bands: %d (expected %d)\n", __func__, n_mel, WHISPER_N_MEL);
return -1;
}
@ -2219,3 +2229,247 @@ void whisper_print_timings(struct whisper_context * ctx) {
printf("%s: decode time = %8.2f ms / %.2f ms per layer\n", __func__, ctx->t_decode_us/1000.0f, ctx->t_decode_us/1000.0f/ctx->model.hparams.n_text_layer);
printf("%s: total time = %8.2f ms\n", __func__, (t_end_us - ctx->t_start_us)/1000.0f);
}
////////////////////////////////////////////////////////////////////////////
struct whisper_full_params whisper_full_default_params(enum whisper_decode_strategy strategy) {
struct whisper_full_params result;
switch (strategy) {
case WHISPER_DECODE_GREEDY:
{
result = (struct whisper_full_params) {
.strategy = WHISPER_DECODE_GREEDY,
.n_threads = std::min(4, (int32_t) std::thread::hardware_concurrency()),
.translate = false,
.print_special_tokens = false,
.print_progress = true,
.language = "en",
.greedy = {
.n_past = 0,
},
};
} break;
case WHISPER_DECODE_BEAM_SEARCH:
{
result = (struct whisper_full_params) {
.strategy = WHISPER_DECODE_GREEDY,
.n_threads = std::min(4, (int32_t) std::thread::hardware_concurrency()),
.translate = false,
.print_special_tokens = false,
.print_progress = true,
.language = "en",
.beam_search = {
.n_past = 0,
.beam_width = 10,
.n_best = 5,
},
};
} break;
}
return result;
}
int whisper_full(
struct whisper_context * ctx,
struct whisper_full_params params,
const float * samples,
int n_samples) {
// compute log mel spectrogram
if (whisper_pcm_to_mel(ctx, samples, n_samples, params.n_threads) != 0) {
fprintf(stderr, "%s: failed to compute log mel spectrogram\n", __func__);
return -1;
}
// the accumulated text context so far
std::vector<whisper_token> prompt_past = { };
// these tokens determine the task that will be performed
std::vector<whisper_token> prompt_init = { whisper_token_sot(ctx) };
if (whisper_is_multilingual(ctx)) {
prompt_init.push_back(whisper_token_sot(ctx) + 1 + whisper_lang_id(params.language));
if (params.translate) {
prompt_init.push_back(whisper_token_translate());
} else {
prompt_init.push_back(whisper_token_transcribe());
}
}
auto & result_all = ctx->result_all;
auto & result_cur = ctx->result_cur;
result_all.clear();
int progress_prev = 0;
int progress_step = 5;
// main loop
int seek = 0;
while (true) {
int progress_cur = (100*seek)/whisper_n_len(ctx);
while (progress_cur >= progress_prev + progress_step) {
progress_prev += progress_step;
if (params.print_progress) {
printf("%s: progress = %3d%%\n", __func__, progress_prev);
}
}
if (seek >= whisper_n_len(ctx)) {
break;
}
// encode audio features starting at offset seek
if (whisper_encode(ctx, seek, params.n_threads) != 0) {
fprintf(stderr, "%s: failed to encode\n", __func__);
return 7;
}
std::vector<whisper_token> prompt;
int n_past = 0;
// if we have already generated some text, use it as a prompt to condition the next generation
if (prompt_past.size() > 0) {
int n_take = std::min(whisper_n_text_ctx(ctx)/2, int(prompt_past.size()));
prompt = { whisper_token_prev(ctx) };
prompt.insert(prompt.begin() + 1, prompt_past.end() - n_take, prompt_past.end());
prompt_past.clear();
prompt_past.insert(prompt_past.end(), prompt.begin() + 1, prompt.end());
}
prompt.insert(prompt.end(), prompt_init.begin(), prompt_init.end());
bool done = false;
int seek_delta = 100*WHISPER_CHUNK_SIZE;
whisper_token last_id = 0;
// print the prompt
//printf("\n\n");
//for (int i = 0; i < prompt.size(); i++) {
// printf("%s: prompt[%d] = %s\n", __func__, i, vocab.id_to_token[prompt[i]].c_str());
//}
//printf("\n\n");
// the accumulated transcription in the current interation
int result_len = 0;
result_cur.clear();
for (int i = 0; i < whisper_n_text_ctx(ctx)/2 - 4; ++i) {
if (whisper_decode(ctx, prompt.data(), prompt.size(), n_past, params.n_threads) != 0) {
fprintf(stderr, "%s: failed to decode\n", __func__);
return 8;
}
n_past += prompt.size();
prompt.clear();
// very basic greedy sampling strategy:
//
// - always take the most probable token
//
// more sophisticated sampling strategies could be implemented here, but we keep it simple
// feel free to experiment!
//
{
const int n_vocab = whisper_n_vocab(ctx);
whisper_token id = 0;
whisper_token tid = whisper_token_beg(ctx);
id = whisper_sample_best(ctx, result_len == 0);
if (i > 0) {
tid = whisper_sample_timestamp(ctx);
}
// update sliding window
if (id > whisper_token_beg(ctx)) {
seek_delta = 2*(id - whisper_token_beg(ctx));
result_len = i + 1;
}
last_id = id;
// add it to the context
prompt.push_back(id);
result_cur.push_back({ seek + 2*(tid - whisper_token_beg(ctx)), id });
//printf("%s: %s\n", __func__, ctx->vocab.id_to_token[id].c_str());
// end of text token
if (id == whisper_token_eot(ctx)) {
if (result_len == 0) {
result_len = i + 1;
}
break;
}
}
if (done) {
break;
}
}
result_cur.resize(result_len);
for (const auto & r : result_cur) {
prompt_past.push_back(r.id);
}
// store the text from this iteration
if (result_cur.size() > 0) {
auto t0 = result_cur.front().t;
std::string text = "";
for (int i = 0; i < result_cur.size(); i++) {
if (params.print_special_tokens == false && result_cur[i].id >= whisper_token_eot(ctx)) {
} else {
text += whisper_token_to_str(ctx, result_cur[i].id);
}
if (result_cur[i].id > whisper_token_beg(ctx)) {
const auto t1 = result_cur[i].t;
if (!text.empty()) {
result_all.push_back({ t0, t1, text });
}
text = "";
while (result_cur[i].id > whisper_token_beg(ctx) && i < result_cur.size()) {
i++;
}
i--;
t0 = result_cur[i].t;
}
}
if (!text.empty()) {
result_all.push_back({ t0, seek + seek_delta, text });
}
}
seek += seek_delta;
}
return 0;
}
int whisper_full_n_segments(struct whisper_context * ctx) {
return ctx->result_all.size();
}
int64_t whisper_full_get_segment_t0(struct whisper_context * ctx, int i_segment) {
return ctx->result_all[i_segment].t0;
}
int64_t whisper_full_get_segment_t1(struct whisper_context * ctx, int i_segment) {
return ctx->result_all[i_segment].t1;
}
const char * whisper_full_get_segment_text(struct whisper_context * ctx, int i_segment) {
return ctx->result_all[i_segment].text.c_str();
}

30
whisper.h
Unescape View File

@ -1,6 +1,8 @@
#ifndef WHISPER_H
#define WHISPER_H
#include <stdint.h>
#ifdef WHISPER_SHARED
# ifdef _WIN32
# ifdef WHISPER_BUILD
@ -15,6 +17,12 @@
# define WHISPER_API
#endif
#define WHISPER_SAMPLE_RATE 16000
#define WHISPER_N_FFT 400
#define WHISPER_N_MEL 80
#define WHISPER_HOP_LENGTH 160
#define WHISPER_CHUNK_SIZE 30
#ifdef __cplusplus
extern "C" {
#endif
@ -23,12 +31,6 @@ extern "C" {
// C interface
//
#define SAMPLE_RATE 16000
#define N_FFT 400
#define N_MEL 80
#define HOP_LENGTH 160
#define CHUNK_SIZE 30
// TODO: documentation will come soon
struct whisper_context;
@ -101,7 +103,9 @@ extern "C" {
int n_threads;
bool transcribe;
bool translate;
bool print_special_tokens;
bool print_progress;
const char * language;
@ -118,14 +122,22 @@ extern "C" {
};
};
WHISPER_API struct whisper_full_params whisper_full_default_params(enum whisper_decode_strategy strategy);
// full whisper run - encode + decode
// TODO: implement
WHISPER_API int whisper_full(
struct whisper_context * ctx,
struct whisper_full_params * params,
struct whisper_full_params params,
const float * samples,
int n_samples);
WHISPER_API int whisper_full_n_segments(struct whisper_context * ctx);
WHISPER_API int64_t whisper_full_get_segment_t0(struct whisper_context * ctx, int i_segment);
WHISPER_API int64_t whisper_full_get_segment_t1(struct whisper_context * ctx, int i_segment);
WHISPER_API const char * whisper_full_get_segment_text(struct whisper_context * ctx, int i_segment);
#ifdef __cplusplus
}
#endif

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