#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) {
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
}
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) {
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;
}
}
}
- // 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");
}
}
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!
- //
- {
- 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)) });
-
- //printf("%s: %s\n", __func__, vocab.id_to_token[id].c_str());
+ // run the inference
+ {
+ whisper_full_params wparams = whisper_full_default_params(WHISPER_DECODE_GREEDY);
- // end of text token
- if (id == whisper_token_eot(ctx)) {
- break;
- }
- }
+ wparams.print_special_tokens = params.print_special_tokens;
- 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)) {
+ if (params.no_timestamps) {
+ printf ("%s", text);
+ fflush(stdout);
} 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());
- 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);
#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) {
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
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;
///////////////////////////
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) {
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;
}
}
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);
}
// 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);
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!
- //
- {
- 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)) });
-
- //printf("%s: %s\n", __func__, vocab.id_to_token[id].c_str());
+ // run the inference
+ {
+ whisper_full_params wparams = whisper_full_default_params(WHISPER_DECODE_GREEDY);
- // end of text token
- if (id == whisper_token_eot(ctx)) {
- break;
- }
- }
+ wparams.print_progress = false;
+ wparams.print_special_tokens = params.print_special_tokens;
- 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)) {
+ if (params.no_timestamps) {
+ printf ("%s", text);
+ fflush(stdout);
} 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());
- 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;
}
}
};
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
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
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) {
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;
}
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;
}
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();
+}
#ifndef WHISPER_H
#define WHISPER_H
+#include <stdint.h>
+
#ifdef WHISPER_SHARED
# ifdef _WIN32
# ifdef WHISPER_BUILD
# 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
// 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;
int n_threads;
- bool transcribe;
+ bool translate;
+ bool print_special_tokens;
+ bool print_progress;
const char * language;
};
};
+ 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
overview / pkg / ggml / sources / whisper.cpp / commitdiff