whisper.cpp/examples/main/main.cpp

1114 lines
47 KiB
C++
Raw Normal View History

#include "common.h"
2022-09-25 20:23:15 +02:00
#include "whisper.h"
#include <cmath>
#include <fstream>
#include <cstdio>
#include <string>
#include <thread>
#include <vector>
2023-03-29 22:59:45 +02:00
#include <cstring>
2023-06-25 13:22:21 +02:00
#if defined(_MSC_VER)
#pragma warning(disable: 4244 4267) // possible loss of data
#endif
// 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()) {
pos = s.find(search, pos);
if (pos == std::string::npos) break;
s.erase(pos, search.length());
s.insert(pos, replace);
}
}
// command-line parameters
struct whisper_params {
int32_t n_threads = std::min(4, (int32_t) std::thread::hardware_concurrency());
int32_t n_processors = 1;
int32_t offset_t_ms = 0;
int32_t offset_n = 0;
int32_t duration_ms = 0;
int32_t progress_step = 5;
int32_t max_context = -1;
int32_t max_len = 0;
int32_t best_of = whisper_full_default_params(WHISPER_SAMPLING_GREEDY).greedy.best_of;
int32_t beam_size = whisper_full_default_params(WHISPER_SAMPLING_BEAM_SEARCH).beam_search.beam_size;
int32_t audio_ctx = 0;
2022-09-25 20:23:15 +02:00
float word_thold = 0.01f;
float entropy_thold = 2.40f;
float logprob_thold = -1.00f;
bool speed_up = false;
whisper : significantly improve the inference quality (#1148) * Fix MSVC compile error C3688 Instead of simply using 'add_compile_options(/utf-8)' to address the MSVC compile error C3688, a better approach would be to handle it in a way that prevents passing '/utf-8' to NVCC. * Significantly improve inference quality In the function `log_mel_spectrogram_worker_thread`, there's an array out-of-bounds issue occurring during the calculation of complex number moduli. This issue is causing disruptions in the FFT spectrum, which, in turn, is reducing the quality of inference. * Significantly improve inference quality At last, I've pinpointed the actual source of the problem. Given that the frequency spectrum generated from real input data is symmetrical around the Nyquist frequency, there's a for-loop within the `log_mel_spectrogram_worker_thread` function that attempts to fold the frequency spectrum. Regrettably, a bug within this for-loop is causing a frame shift in the frequency spectrum. The previous attempt to remedy this, which involved using `fft_size + 1` when calculating the modulus, was merely a band-aid solution and did not address the underlying issue. * Addressed a few minor issues Fixed the issue of `fft_out` continuously expanding. Resolved the fallback caused by using 'break' instead of `fft_in[j] = 0`. * Significantly improve inference quality Thanks for your patience everyone. It's finally sorted out. Now, the right side of the FFT spectrum is being flipped over to the left, and the amplitudes at corresponding positions on the left and right are added together (the spectrum on the left needs to be shifted by one position), then the average is calculated. FFT_OUT[0] is no longer discarded, making full use of the limited space to pack in more information. * Add annotation and performance improvement * Calculate FFT only when fft_in are not all zero * Some minor performance improvement * Fixed a bug impacting inference quality * The first version after all the analysis is completed. * Fix some bugs and add debug mode * Fixed several bugs * Temporarily disable speed-up mode and add debug mode. * Add debug mode * Disable speed-up mode and add debug mode * Fix CI error (#1) * Fix error * Fix error * Fixed several bugs including [BLANK_AUDIO] problem * Remove Hard-coded hann window * Some Final Fix (#2) * Fix error * Fix error * Probably the last commit * Probably the last commit * whisper : minor coding style changes * whisper : remove debug from public API --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-08-27 18:51:33 +02:00
bool debug_mode = false;
bool translate = false;
bool detect_language = false;
bool diarize = false;
bool tinydiarize = false;
bool split_on_word = false;
bool no_fallback = false;
bool output_txt = false;
bool output_vtt = false;
bool output_srt = false;
bool output_wts = false;
bool output_csv = false;
bool output_jsn = false;
bool output_jsn_full = false;
bool output_lrc = false;
bool no_prints = false;
bool print_special = false;
bool print_colors = false;
bool print_progress = false;
bool no_timestamps = false;
bool log_score = false;
bool use_gpu = true;
std::string language = "en";
std::string prompt;
std::string font_path = "/System/Library/Fonts/Supplemental/Courier New Bold.ttf";
std::string model = "models/ggml-base.en.bin";
// [TDRZ] speaker turn string
std::string tdrz_speaker_turn = " [SPEAKER_TURN]"; // TODO: set from command line
std::string openvino_encode_device = "CPU";
std::string dtw = "";
std::vector<std::string> fname_inp = {};
std::vector<std::string> fname_out = {};
};
2022-09-25 20:23:15 +02:00
void whisper_print_usage(int argc, char ** argv, const whisper_params & params);
2022-09-25 20:23:15 +02:00
char* whisper_param_turn_lowercase(char* in){
int string_len = strlen(in);
for(int i = 0; i < string_len; i++){
*(in+i) = tolower((unsigned char)*(in+i));
}
return in;
}
bool whisper_params_parse(int argc, char ** argv, whisper_params & params) {
for (int i = 1; i < argc; i++) {
std::string arg = argv[i];
2023-02-18 08:42:31 +01:00
if (arg == "-"){
params.fname_inp.push_back(arg);
continue;
}
2023-02-18 08:42:31 +01:00
if (arg[0] != '-') {
params.fname_inp.push_back(arg);
continue;
}
2022-11-25 18:08:51 +01:00
if (arg == "-h" || arg == "--help") {
whisper_print_usage(argc, argv, params);
exit(0);
2022-11-25 18:08:51 +01:00
}
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 == "-bo" || arg == "--best-of") { params.best_of = std::stoi(argv[++i]); }
else if (arg == "-bs" || arg == "--beam-size") { params.beam_size = std::stoi(argv[++i]); }
else if (arg == "-ac" || arg == "--audio-ctx") { params.audio_ctx = std::stoi(argv[++i]); }
else if (arg == "-wt" || arg == "--word-thold") { params.word_thold = std::stof(argv[++i]); }
else if (arg == "-et" || arg == "--entropy-thold") { params.entropy_thold = std::stof(argv[++i]); }
else if (arg == "-lpt" || arg == "--logprob-thold") { params.logprob_thold = std::stof(argv[++i]); }
whisper : significantly improve the inference quality (#1148) * Fix MSVC compile error C3688 Instead of simply using 'add_compile_options(/utf-8)' to address the MSVC compile error C3688, a better approach would be to handle it in a way that prevents passing '/utf-8' to NVCC. * Significantly improve inference quality In the function `log_mel_spectrogram_worker_thread`, there's an array out-of-bounds issue occurring during the calculation of complex number moduli. This issue is causing disruptions in the FFT spectrum, which, in turn, is reducing the quality of inference. * Significantly improve inference quality At last, I've pinpointed the actual source of the problem. Given that the frequency spectrum generated from real input data is symmetrical around the Nyquist frequency, there's a for-loop within the `log_mel_spectrogram_worker_thread` function that attempts to fold the frequency spectrum. Regrettably, a bug within this for-loop is causing a frame shift in the frequency spectrum. The previous attempt to remedy this, which involved using `fft_size + 1` when calculating the modulus, was merely a band-aid solution and did not address the underlying issue. * Addressed a few minor issues Fixed the issue of `fft_out` continuously expanding. Resolved the fallback caused by using 'break' instead of `fft_in[j] = 0`. * Significantly improve inference quality Thanks for your patience everyone. It's finally sorted out. Now, the right side of the FFT spectrum is being flipped over to the left, and the amplitudes at corresponding positions on the left and right are added together (the spectrum on the left needs to be shifted by one position), then the average is calculated. FFT_OUT[0] is no longer discarded, making full use of the limited space to pack in more information. * Add annotation and performance improvement * Calculate FFT only when fft_in are not all zero * Some minor performance improvement * Fixed a bug impacting inference quality * The first version after all the analysis is completed. * Fix some bugs and add debug mode * Fixed several bugs * Temporarily disable speed-up mode and add debug mode. * Add debug mode * Disable speed-up mode and add debug mode * Fix CI error (#1) * Fix error * Fix error * Fixed several bugs including [BLANK_AUDIO] problem * Remove Hard-coded hann window * Some Final Fix (#2) * Fix error * Fix error * Probably the last commit * Probably the last commit * whisper : minor coding style changes * whisper : remove debug from public API --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-08-27 18:51:33 +02:00
// else if (arg == "-su" || arg == "--speed-up") { params.speed_up = true; }
else if (arg == "-debug"|| arg == "--debug-mode") { params.debug_mode = true; }
else if (arg == "-tr" || arg == "--translate") { params.translate = true; }
else if (arg == "-di" || arg == "--diarize") { params.diarize = true; }
else if (arg == "-tdrz" || arg == "--tinydiarize") { params.tinydiarize = true; }
else if (arg == "-sow" || arg == "--split-on-word") { params.split_on_word = true; }
else if (arg == "-nf" || arg == "--no-fallback") { params.no_fallback = 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 == "-olrc" || arg == "--output-lrc") { params.output_lrc = true; }
else if (arg == "-fp" || arg == "--font-path") { params.font_path = argv[++i]; }
else if (arg == "-ocsv" || arg == "--output-csv") { params.output_csv = true; }
else if (arg == "-oj" || arg == "--output-json") { params.output_jsn = true; }
else if (arg == "-ojf" || arg == "--output-json-full"){ params.output_jsn_full = params.output_jsn = true; }
else if (arg == "-of" || arg == "--output-file") { params.fname_out.emplace_back(argv[++i]); }
else if (arg == "-np" || arg == "--no-prints") { params.no_prints = 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 == "-pp" || arg == "--print-progress") { params.print_progress = true; }
else if (arg == "-nt" || arg == "--no-timestamps") { params.no_timestamps = true; }
else if (arg == "-l" || arg == "--language") { params.language = whisper_param_turn_lowercase(argv[++i]); }
else if (arg == "-dl" || arg == "--detect-language") { params.detect_language = true; }
else if ( arg == "--prompt") { params.prompt = argv[++i]; }
else if (arg == "-m" || arg == "--model") { params.model = argv[++i]; }
else if (arg == "-f" || arg == "--file") { params.fname_inp.emplace_back(argv[++i]); }
else if (arg == "-oved" || arg == "--ov-e-device") { params.openvino_encode_device = argv[++i]; }
else if (arg == "-dtw" || arg == "--dtw") { params.dtw = argv[++i]; }
else if (arg == "-ls" || arg == "--log-score") { params.log_score = true; }
else if (arg == "-ng" || arg == "--no-gpu") { params.use_gpu = false; }
2022-11-25 18:08:51 +01:00
else {
fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
2023-06-25 13:22:21 +02:00
whisper_print_usage(argc, argv, params);
exit(0);
2022-09-25 20:23:15 +02:00
}
}
return true;
}
void whisper_print_usage(int /*argc*/, char ** argv, const whisper_params & params) {
fprintf(stderr, "\n");
fprintf(stderr, "usage: %s [options] file0.wav file1.wav ...\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, " -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, " -sow, --split-on-word [%-7s] split on word rather than on token\n", params.split_on_word ? "true" : "false");
fprintf(stderr, " -bo N, --best-of N [%-7d] number of best candidates to keep\n", params.best_of);
fprintf(stderr, " -bs N, --beam-size N [%-7d] beam size for beam search\n", params.beam_size);
fprintf(stderr, " -ac N, --audio-ctx N [%-7d] audio context size (0 - all)\n", params.audio_ctx);
fprintf(stderr, " -wt N, --word-thold N [%-7.2f] word timestamp probability threshold\n", params.word_thold);
fprintf(stderr, " -et N, --entropy-thold N [%-7.2f] entropy threshold for decoder fail\n", params.entropy_thold);
fprintf(stderr, " -lpt N, --logprob-thold N [%-7.2f] log probability threshold for decoder fail\n", params.logprob_thold);
whisper : significantly improve the inference quality (#1148) * Fix MSVC compile error C3688 Instead of simply using 'add_compile_options(/utf-8)' to address the MSVC compile error C3688, a better approach would be to handle it in a way that prevents passing '/utf-8' to NVCC. * Significantly improve inference quality In the function `log_mel_spectrogram_worker_thread`, there's an array out-of-bounds issue occurring during the calculation of complex number moduli. This issue is causing disruptions in the FFT spectrum, which, in turn, is reducing the quality of inference. * Significantly improve inference quality At last, I've pinpointed the actual source of the problem. Given that the frequency spectrum generated from real input data is symmetrical around the Nyquist frequency, there's a for-loop within the `log_mel_spectrogram_worker_thread` function that attempts to fold the frequency spectrum. Regrettably, a bug within this for-loop is causing a frame shift in the frequency spectrum. The previous attempt to remedy this, which involved using `fft_size + 1` when calculating the modulus, was merely a band-aid solution and did not address the underlying issue. * Addressed a few minor issues Fixed the issue of `fft_out` continuously expanding. Resolved the fallback caused by using 'break' instead of `fft_in[j] = 0`. * Significantly improve inference quality Thanks for your patience everyone. It's finally sorted out. Now, the right side of the FFT spectrum is being flipped over to the left, and the amplitudes at corresponding positions on the left and right are added together (the spectrum on the left needs to be shifted by one position), then the average is calculated. FFT_OUT[0] is no longer discarded, making full use of the limited space to pack in more information. * Add annotation and performance improvement * Calculate FFT only when fft_in are not all zero * Some minor performance improvement * Fixed a bug impacting inference quality * The first version after all the analysis is completed. * Fix some bugs and add debug mode * Fixed several bugs * Temporarily disable speed-up mode and add debug mode. * Add debug mode * Disable speed-up mode and add debug mode * Fix CI error (#1) * Fix error * Fix error * Fixed several bugs including [BLANK_AUDIO] problem * Remove Hard-coded hann window * Some Final Fix (#2) * Fix error * Fix error * Probably the last commit * Probably the last commit * whisper : minor coding style changes * whisper : remove debug from public API --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-08-27 18:51:33 +02:00
// fprintf(stderr, " -su, --speed-up [%-7s] speed up audio by x2 (reduced accuracy)\n", params.speed_up ? "true" : "false");
fprintf(stderr, " -debug, --debug-mode [%-7s] enable debug mode (eg. dump log_mel)\n", params.debug_mode ? "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, " -tdrz, --tinydiarize [%-7s] enable tinydiarize (requires a tdrz model)\n", params.tinydiarize ? "true" : "false");
fprintf(stderr, " -nf, --no-fallback [%-7s] do not use temperature fallback while decoding\n", params.no_fallback ? "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, " -olrc, --output-lrc [%-7s] output result in a lrc file\n", params.output_lrc ? "true" : "false");
fprintf(stderr, " -owts, --output-words [%-7s] output script for generating karaoke video\n", params.output_wts ? "true" : "false");
fprintf(stderr, " -fp, --font-path [%-7s] path to a monospace font for karaoke video\n", params.font_path.c_str());
fprintf(stderr, " -ocsv, --output-csv [%-7s] output result in a CSV file\n", params.output_csv ? "true" : "false");
fprintf(stderr, " -oj, --output-json [%-7s] output result in a JSON file\n", params.output_jsn ? "true" : "false");
fprintf(stderr, " -ojf, --output-json-full [%-7s] include more information in the JSON file\n", params.output_jsn_full ? "true" : "false");
fprintf(stderr, " -of FNAME, --output-file FNAME [%-7s] output file path (without file extension)\n", "");
fprintf(stderr, " -np, --no-prints [%-7s] do not print anything other than the results\n", params.no_prints ? "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, " -pp, --print-progress [%-7s] print progress\n", params.print_progress ? "true" : "false");
fprintf(stderr, " -nt, --no-timestamps [%-7s] do not print timestamps\n", params.no_timestamps ? "true" : "false");
fprintf(stderr, " -l LANG, --language LANG [%-7s] spoken language ('auto' for auto-detect)\n", params.language.c_str());
fprintf(stderr, " -dl, --detect-language [%-7s] exit after automatically detecting language\n", params.detect_language ? "true" : "false");
fprintf(stderr, " --prompt PROMPT [%-7s] initial prompt (max n_text_ctx/2 tokens)\n", params.prompt.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, " -oved D, --ov-e-device DNAME [%-7s] the OpenVINO device used for encode inference\n", params.openvino_encode_device.c_str());
fprintf(stderr, " -dtw MODEL --dtw MODEL [%-7s] compute token-level timestamps\n", params.dtw.c_str());
fprintf(stderr, " -ls, --log-score [%-7s] log best decoder scores of tokens\n", params.log_score?"true":"false");
fprintf(stderr, " -ng, --no-gpu [%-7s] disable GPU\n", params.use_gpu ? "false" : "true");
fprintf(stderr, "\n");
}
struct whisper_print_user_data {
const whisper_params * params;
const std::vector<std::vector<float>> * pcmf32s;
int progress_prev;
};
std::string estimate_diarization_speaker(std::vector<std::vector<float>> pcmf32s, int64_t t0, int64_t t1, bool id_only = false) {
std::string speaker = "";
const int64_t n_samples = pcmf32s[0].size();
const int64_t is0 = timestamp_to_sample(t0, n_samples, WHISPER_SAMPLE_RATE);
const int64_t is1 = timestamp_to_sample(t1, n_samples, WHISPER_SAMPLE_RATE);
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 = "0";
} else if (energy1 > 1.1*energy0) {
speaker = "1";
} else {
speaker = "?";
}
//printf("is0 = %lld, is1 = %lld, energy0 = %f, energy1 = %f, speaker = %s\n", is0, is1, energy0, energy1, speaker.c_str());
if (!id_only) {
speaker.insert(0, "(speaker ");
speaker.append(")");
}
return speaker;
}
void whisper_print_progress_callback(struct whisper_context * /*ctx*/, struct whisper_state * /*state*/, int progress, void * user_data) {
int progress_step = ((whisper_print_user_data *) user_data)->params->progress_step;
int * progress_prev = &(((whisper_print_user_data *) user_data)->progress_prev);
if (progress >= *progress_prev + progress_step) {
*progress_prev += progress_step;
fprintf(stderr, "%s: progress = %3d%%\n", __func__, progress);
}
}
void whisper_print_segment_callback(struct whisper_context * ctx, struct whisper_state * /*state*/, int n_new, void * 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);
std::string speaker = "";
int64_t t0 = 0;
int64_t t1 = 0;
// print the last n_new segments
const int s0 = n_segments - n_new;
if (s0 == 0) {
printf("\n");
}
for (int i = s0; i < n_segments; i++) {
if (!params.no_timestamps || params.diarize) {
t0 = whisper_full_get_segment_t0(ctx, i);
t1 = whisper_full_get_segment_t1(ctx, i);
}
2022-10-22 20:09:30 +02:00
if (!params.no_timestamps) {
printf("[%s --> %s] ", to_timestamp(t0).c_str(), to_timestamp(t1).c_str());
}
2022-10-22 20:09:30 +02:00
if (params.diarize && pcmf32s.size() == 2) {
speaker = estimate_diarization_speaker(pcmf32s, t0, t1);
}
if (params.print_colors) {
for (int j = 0; j < whisper_full_n_tokens(ctx, i); ++j) {
if (params.print_special == false) {
const whisper_token id = whisper_full_get_token_id(ctx, i, j);
if (id >= whisper_token_eot(ctx)) {
continue;
}
}
const char * text = whisper_full_get_token_text(ctx, i, j);
const float p = whisper_full_get_token_p (ctx, i, j);
const int col = std::max(0, std::min((int) k_colors.size() - 1, (int) (std::pow(p, 3)*float(k_colors.size()))));
printf("%s%s%s%s", speaker.c_str(), k_colors[col].c_str(), text, "\033[0m");
}
} else {
const char * text = whisper_full_get_segment_text(ctx, i);
printf("%s%s", speaker.c_str(), text);
}
if (params.tinydiarize) {
if (whisper_full_get_segment_speaker_turn_next(ctx, i)) {
printf("%s", params.tdrz_speaker_turn.c_str());
}
}
// with timestamps or speakers: each segment on new line
if (!params.no_timestamps || params.diarize) {
printf("\n");
}
fflush(stdout);
}
}
bool output_txt(struct whisper_context * ctx, const char * fname, const whisper_params & params, std::vector<std::vector<float>> pcmf32s) {
2022-10-22 19:42:11 +02:00
std::ofstream fout(fname);
if (!fout.is_open()) {
fprintf(stderr, "%s: failed to open '%s' for writing\n", __func__, fname);
return false;
}
fprintf(stderr, "%s: saving output to '%s'\n", __func__, fname);
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 speaker = "";
if (params.diarize && pcmf32s.size() == 2)
{
const int64_t t0 = whisper_full_get_segment_t0(ctx, i);
const int64_t t1 = whisper_full_get_segment_t1(ctx, i);
speaker = estimate_diarization_speaker(pcmf32s, t0, t1);
}
fout << speaker << text << "\n";
2022-10-22 19:42:11 +02:00
}
return true;
}
bool output_vtt(struct whisper_context * ctx, const char * fname, const whisper_params & params, std::vector<std::vector<float>> pcmf32s) {
2022-10-22 19:42:11 +02:00
std::ofstream fout(fname);
if (!fout.is_open()) {
fprintf(stderr, "%s: failed to open '%s' for writing\n", __func__, fname);
return false;
2022-10-22 19:42:11 +02:00
}
fprintf(stderr, "%s: saving output to '%s'\n", __func__, fname);
fout << "WEBVTT\n\n";
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);
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)
{
speaker = estimate_diarization_speaker(pcmf32s, t0, t1, true);
speaker.insert(0, "<v Speaker");
speaker.append(">");
}
2022-10-22 19:42:11 +02:00
fout << to_timestamp(t0) << " --> " << to_timestamp(t1) << "\n";
fout << speaker << text << "\n\n";
2022-10-22 19:42:11 +02:00
}
return true;
}
bool output_srt(struct whisper_context * ctx, const char * fname, const whisper_params & params, std::vector<std::vector<float>> pcmf32s) {
2022-10-22 19:42:11 +02:00
std::ofstream fout(fname);
if (!fout.is_open()) {
fprintf(stderr, "%s: failed to open '%s' for writing\n", __func__, fname);
return false;
}
fprintf(stderr, "%s: saving output to '%s'\n", __func__, fname);
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);
2022-10-23 12:29:36 +02:00
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)
{
speaker = estimate_diarization_speaker(pcmf32s, t0, t1);
}
2022-10-23 12:29:36 +02:00
fout << i + 1 + params.offset_n << "\n";
fout << to_timestamp(t0, true) << " --> " << to_timestamp(t1, true) << "\n";
fout << speaker << text << "\n\n";
2022-10-22 19:42:11 +02:00
}
return true;
}
char *escape_double_quotes_and_backslashes(const char *str) {
if (str == NULL) {
return NULL;
}
size_t escaped_length = strlen(str) + 1;
for (size_t i = 0; str[i] != '\0'; i++) {
if (str[i] == '"' || str[i] == '\\') {
escaped_length++;
}
}
char *escaped = (char *)calloc(escaped_length, 1); // pre-zeroed
if (escaped == NULL) {
return NULL;
}
size_t pos = 0;
for (size_t i = 0; str[i] != '\0'; i++) {
if (str[i] == '"' || str[i] == '\\') {
escaped[pos++] = '\\';
}
escaped[pos++] = str[i];
}
// no need to set zero due to calloc() being used prior
return escaped;
}
bool output_csv(struct whisper_context * ctx, const char * fname, const whisper_params & params, std::vector<std::vector<float>> pcmf32s) {
std::ofstream fout(fname);
if (!fout.is_open()) {
fprintf(stderr, "%s: failed to open '%s' for writing\n", __func__, fname);
return false;
}
fprintf(stderr, "%s: saving output to '%s'\n", __func__, fname);
const int n_segments = whisper_full_n_segments(ctx);
fout << "start,end,";
if (params.diarize && pcmf32s.size() == 2)
{
fout << "speaker,";
}
fout << "text\n";
for (int i = 0; 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);
char * text_escaped = escape_double_quotes_and_backslashes(text);
//need to multiply times returned from whisper_full_get_segment_t{0,1}() by 10 to get milliseconds.
fout << 10 * t0 << "," << 10 * t1 << ",";
if (params.diarize && pcmf32s.size() == 2)
{
fout << estimate_diarization_speaker(pcmf32s, t0, t1, true) << ",";
}
fout << "\"" << text_escaped << "\"\n";
}
return true;
}
bool output_score(struct whisper_context * ctx, const char * fname, const whisper_params & /*params*/, std::vector<std::vector<float>> /*pcmf32s*/) {
std::ofstream fout(fname);
fprintf(stderr, "%s: saving output to '%s'\n", __func__, fname);
const int n_segments = whisper_full_n_segments(ctx);
// fprintf(stderr,"segments: %d\n",n_segments);
for (int i = 0; i < n_segments; ++i) {
const int n_tokens = whisper_full_n_tokens(ctx, i);
// fprintf(stderr,"tokens: %d\n",n_tokens);
for (int j = 0; j < n_tokens; j++) {
auto token = whisper_full_get_token_text(ctx, i, j);
auto probability = whisper_full_get_token_p(ctx, i, j);
fout << token << '\t' << probability << std::endl;
// fprintf(stderr,"token: %s %f\n",token,probability);
}
}
return true;
}
bool output_json(
struct whisper_context * ctx,
const char * fname,
const whisper_params & params,
std::vector<std::vector<float>> pcmf32s,
bool full) {
std::ofstream fout(fname);
int indent = 0;
auto doindent = [&]() {
for (int i = 0; i < indent; i++) fout << "\t";
};
auto start_arr = [&](const char *name) {
doindent();
fout << "\"" << name << "\": [\n";
indent++;
};
2023-06-25 13:22:21 +02:00
auto end_arr = [&](bool end) {
indent--;
doindent();
fout << (end ? "]\n" : "],\n");
};
2023-06-25 13:22:21 +02:00
auto start_obj = [&](const char *name) {
doindent();
if (name) {
fout << "\"" << name << "\": {\n";
} else {
fout << "{\n";
}
indent++;
};
2023-06-25 13:22:21 +02:00
auto end_obj = [&](bool end) {
indent--;
doindent();
fout << (end ? "}\n" : "},\n");
};
auto start_value = [&](const char *name) {
doindent();
fout << "\"" << name << "\": ";
};
2023-06-25 13:22:21 +02:00
auto value_s = [&](const char *name, const char *val, bool end) {
start_value(name);
char * val_escaped = escape_double_quotes_and_backslashes(val);
fout << "\"" << val_escaped << (end ? "\"\n" : "\",\n");
free(val_escaped);
};
2023-06-25 13:22:21 +02:00
auto end_value = [&](bool end) {
fout << (end ? "\n" : ",\n");
};
2023-06-25 13:22:21 +02:00
auto value_i = [&](const char *name, const int64_t val, bool end) {
start_value(name);
fout << val;
end_value(end);
};
auto value_f = [&](const char *name, const float val, bool end) {
start_value(name);
fout << val;
end_value(end);
};
2023-06-25 13:22:21 +02:00
auto value_b = [&](const char *name, const bool val, bool end) {
start_value(name);
fout << (val ? "true" : "false");
end_value(end);
};
auto times_o = [&](int64_t t0, int64_t t1, bool end) {
start_obj("timestamps");
value_s("from", to_timestamp(t0, true).c_str(), false);
value_s("to", to_timestamp(t1, true).c_str(), true);
end_obj(false);
start_obj("offsets");
value_i("from", t0 * 10, false);
value_i("to", t1 * 10, true);
end_obj(end);
};
if (!fout.is_open()) {
fprintf(stderr, "%s: failed to open '%s' for writing\n", __func__, fname);
return false;
}
fprintf(stderr, "%s: saving output to '%s'\n", __func__, fname);
2023-06-25 13:22:21 +02:00
start_obj(nullptr);
value_s("systeminfo", whisper_print_system_info(), false);
start_obj("model");
2023-06-25 13:22:21 +02:00
value_s("type", whisper_model_type_readable(ctx), false);
value_b("multilingual", whisper_is_multilingual(ctx), false);
value_i("vocab", whisper_model_n_vocab(ctx), false);
start_obj("audio");
2023-06-25 13:22:21 +02:00
value_i("ctx", whisper_model_n_audio_ctx(ctx), false);
value_i("state", whisper_model_n_audio_state(ctx), false);
value_i("head", whisper_model_n_audio_head(ctx), false);
value_i("layer", whisper_model_n_audio_layer(ctx), true);
2023-06-25 13:22:21 +02:00
end_obj(false);
start_obj("text");
2023-06-25 13:22:21 +02:00
value_i("ctx", whisper_model_n_text_ctx(ctx), false);
value_i("state", whisper_model_n_text_state(ctx), false);
value_i("head", whisper_model_n_text_head(ctx), false);
value_i("layer", whisper_model_n_text_layer(ctx), true);
2023-06-25 13:22:21 +02:00
end_obj(false);
value_i("mels", whisper_model_n_mels(ctx), false);
value_i("ftype", whisper_model_ftype(ctx), true);
2023-06-25 13:22:21 +02:00
end_obj(false);
start_obj("params");
2023-06-25 13:22:21 +02:00
value_s("model", params.model.c_str(), false);
value_s("language", params.language.c_str(), false);
value_b("translate", params.translate, true);
2023-06-25 13:22:21 +02:00
end_obj(false);
start_obj("result");
value_s("language", whisper_lang_str(whisper_full_lang_id(ctx)), true);
2023-06-25 13:22:21 +02:00
end_obj(false);
start_arr("transcription");
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);
const int64_t t0 = whisper_full_get_segment_t0(ctx, i);
const int64_t t1 = whisper_full_get_segment_t1(ctx, i);
2023-06-25 13:22:21 +02:00
start_obj(nullptr);
times_o(t0, t1, false);
value_s("text", text, !params.diarize && !params.tinydiarize && !full);
if (full) {
start_arr("tokens");
const int n = whisper_full_n_tokens(ctx, i);
for (int j = 0; j < n; ++j) {
auto token = whisper_full_get_token_data(ctx, i, j);
start_obj(nullptr);
value_s("text", whisper_token_to_str(ctx, token.id), false);
if(token.t0 > -1 && token.t1 > -1) {
// If we have per-token timestamps, write them out
times_o(token.t0, token.t1, false);
}
value_i("id", token.id, false);
value_f("p", token.p, false);
value_f("t_dtw", token.t_dtw, true);
end_obj(j == (n - 1));
}
end_arr(!params.diarize && !params.tinydiarize);
}
if (params.diarize && pcmf32s.size() == 2) {
value_s("speaker", estimate_diarization_speaker(pcmf32s, t0, t1, true).c_str(), true);
}
if (params.tinydiarize) {
value_b("speaker_turn_next", whisper_full_get_segment_speaker_turn_next(ctx, i), true);
}
end_obj(i == (n_segments - 1));
}
end_arr(true);
end_obj(true);
return true;
}
// karaoke video generation
// outputs a bash script that uses ffmpeg to generate a video with the subtitles
// TODO: font parameter adjustments
bool output_wts(struct whisper_context * ctx, const char * fname, const char * fname_inp, const whisper_params & params, float t_sec, std::vector<std::vector<float>> pcmf32s) {
std::ofstream fout(fname);
fprintf(stderr, "%s: saving output to '%s'\n", __func__, fname);
static const char * font = params.font_path.c_str();
std::ifstream fin(font);
if (!fin.is_open()) {
fprintf(stderr, "%s: font not found at '%s', please specify a monospace font with -fp\n", __func__, font);
return false;
}
2022-11-04 17:30:38 +01:00
fout << "#!/bin/bash" << "\n";
fout << "\n";
fout << "ffmpeg -i " << fname_inp << " -f lavfi -i color=size=1200x120:duration=" << t_sec << ":rate=25:color=black -vf \"";
for (int i = 0; i < whisper_full_n_segments(ctx); i++) {
const int64_t t0 = whisper_full_get_segment_t0(ctx, i);
const int64_t t1 = whisper_full_get_segment_t1(ctx, i);
const int n = whisper_full_n_tokens(ctx, i);
std::vector<whisper_token_data> tokens(n);
for (int j = 0; j < n; ++j) {
tokens[j] = whisper_full_get_token_data(ctx, i, j);
}
if (i > 0) {
fout << ",";
}
// background text
fout << "drawtext=fontfile='" << font << "':fontsize=24:fontcolor=gray:x=(w-text_w)/2:y=h/2:text='':enable='between(t," << t0/100.0 << "," << t0/100.0 << ")'";
bool is_first = true;
std::string speaker = "";
if (params.diarize && pcmf32s.size() == 2) {
speaker = estimate_diarization_speaker(pcmf32s, t0, t1);
}
for (int j = 0; j < n; ++j) {
const auto & token = tokens[j];
if (tokens[j].id >= whisper_token_eot(ctx)) {
continue;
}
std::string txt_bg = "";
std::string txt_fg = ""; // highlight token
std::string txt_ul = ""; // underline
if (params.diarize && pcmf32s.size() == 2) {
txt_bg = speaker;
txt_fg = speaker;
txt_ul = "\\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ ";
}
txt_bg.append("> ");
txt_fg.append("> ");
txt_ul.append("\\ \\ ");
{
for (int k = 0; k < n; ++k) {
const auto & token2 = tokens[k];
if (tokens[k].id >= whisper_token_eot(ctx)) {
continue;
}
const std::string txt = whisper_token_to_str(ctx, token2.id);
txt_bg += txt;
if (k == j) {
for (int l = 0; l < (int) txt.size(); ++l) {
txt_fg += txt[l];
txt_ul += "_";
}
txt_fg += "|";
} else {
for (int l = 0; l < (int) txt.size(); ++l) {
txt_fg += "\\ ";
txt_ul += "\\ ";
}
}
}
::replace_all(txt_bg, "'", "\u2019");
::replace_all(txt_bg, "\"", "\\\"");
::replace_all(txt_fg, "'", "\u2019");
::replace_all(txt_fg, "\"", "\\\"");
}
if (is_first) {
// background text
fout << ",drawtext=fontfile='" << font << "':fontsize=24:fontcolor=gray:x=(w-text_w)/2:y=h/2:text='" << txt_bg << "':enable='between(t," << t0/100.0 << "," << t1/100.0 << ")'";
is_first = false;
}
// foreground text
fout << ",drawtext=fontfile='" << font << "':fontsize=24:fontcolor=lightgreen:x=(w-text_w)/2+8:y=h/2:text='" << txt_fg << "':enable='between(t," << token.t0/100.0 << "," << token.t1/100.0 << ")'";
// underline
fout << ",drawtext=fontfile='" << font << "':fontsize=24:fontcolor=lightgreen:x=(w-text_w)/2+8:y=h/2+16:text='" << txt_ul << "':enable='between(t," << token.t0/100.0 << "," << token.t1/100.0 << ")'";
}
}
fout << "\" -c:v libx264 -pix_fmt yuv420p -y " << fname_inp << ".mp4" << "\n";
fout << "\n\n";
fout << "echo \"Your video has been saved to " << fname_inp << ".mp4\"" << "\n";
fout << "\n";
fout << "echo \" ffplay " << fname_inp << ".mp4\"\n";
fout << "\n";
fout.close();
fprintf(stderr, "%s: run 'source %s' to generate karaoke video\n", __func__, fname);
return true;
}
bool output_lrc(struct whisper_context * ctx, const char * fname, const whisper_params & params, std::vector<std::vector<float>> pcmf32s) {
std::ofstream fout(fname);
if (!fout.is_open()) {
fprintf(stderr, "%s: failed to open '%s' for writing\n", __func__, fname);
return false;
}
fprintf(stderr, "%s: saving output to '%s'\n", __func__, fname);
fout << "[by:whisper.cpp]\n";
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);
const int64_t t = whisper_full_get_segment_t0(ctx, i);
int64_t msec = t * 10;
int64_t min = msec / (1000 * 60);
msec = msec - min * (1000 * 60);
int64_t sec = msec / 1000;
msec = msec - sec * 1000;
char buf[16];
snprintf(buf, sizeof(buf), "%02d:%02d.%02d", (int) min, (int) sec, (int) ( msec / 10));
std::string timestamp_lrc = std::string(buf);
std::string speaker = "";
if (params.diarize && pcmf32s.size() == 2)
{
const int64_t t0 = whisper_full_get_segment_t0(ctx, i);
const int64_t t1 = whisper_full_get_segment_t1(ctx, i);
speaker = estimate_diarization_speaker(pcmf32s, t0, t1);
}
fout << '[' << timestamp_lrc << ']' << speaker << text << "\n";
}
return true;
}
void cb_log_disable(enum ggml_log_level , const char * , void * ) { }
2022-09-25 20:23:15 +02:00
int main(int argc, char ** argv) {
whisper_params params;
if (whisper_params_parse(argc, argv, params) == false) {
whisper_print_usage(argc, argv, params);
2022-09-25 20:23:15 +02:00
return 1;
}
// remove non-existent files
for (auto it = params.fname_inp.begin(); it != params.fname_inp.end();) {
const auto fname_inp = it->c_str();
if (*it != "-" && !is_file_exist(fname_inp)) {
fprintf(stderr, "error: input file not found '%s'\n", fname_inp);
it = params.fname_inp.erase(it);
continue;
}
it++;
}
if (params.fname_inp.empty()) {
fprintf(stderr, "error: no input files specified\n");
whisper_print_usage(argc, argv, params);
return 2;
}
2022-12-17 16:58:08 +01:00
if (params.language != "auto" && whisper_lang_id(params.language.c_str()) == -1) {
2022-11-25 18:08:51 +01:00
fprintf(stderr, "error: unknown language '%s'\n", params.language.c_str());
whisper_print_usage(argc, argv, params);
exit(0);
}
if (params.diarize && params.tinydiarize) {
fprintf(stderr, "error: cannot use both --diarize and --tinydiarize\n");
whisper_print_usage(argc, argv, params);
exit(0);
}
if (params.no_prints) {
whisper_log_set(cb_log_disable, NULL);
}
// whisper init
2022-09-25 20:23:15 +02:00
struct whisper_context_params cparams = whisper_context_default_params();
cparams.use_gpu = params.use_gpu;
if (!params.dtw.empty()) {
cparams.dtw_token_timestamps = true;
cparams.dtw_aheads_preset = WHISPER_AHEADS_NONE;
if (params.dtw == "tiny") cparams.dtw_aheads_preset = WHISPER_AHEADS_TINY;
if (params.dtw == "tiny.en") cparams.dtw_aheads_preset = WHISPER_AHEADS_TINY_EN;
if (params.dtw == "base") cparams.dtw_aheads_preset = WHISPER_AHEADS_BASE;
if (params.dtw == "base.en") cparams.dtw_aheads_preset = WHISPER_AHEADS_BASE_EN;
if (params.dtw == "small") cparams.dtw_aheads_preset = WHISPER_AHEADS_SMALL;
if (params.dtw == "small.en") cparams.dtw_aheads_preset = WHISPER_AHEADS_SMALL_EN;
if (params.dtw == "medium") cparams.dtw_aheads_preset = WHISPER_AHEADS_MEDIUM;
if (params.dtw == "medium.en") cparams.dtw_aheads_preset = WHISPER_AHEADS_MEDIUM_EN;
if (params.dtw == "large.v1") cparams.dtw_aheads_preset = WHISPER_AHEADS_LARGE_V1;
if (params.dtw == "large.v2") cparams.dtw_aheads_preset = WHISPER_AHEADS_LARGE_V2;
if (params.dtw == "large.v3") cparams.dtw_aheads_preset = WHISPER_AHEADS_LARGE_V3;
if (cparams.dtw_aheads_preset == WHISPER_AHEADS_NONE) {
fprintf(stderr, "error: unknown DTW preset '%s'\n", params.dtw.c_str());
return 3;
}
}
struct whisper_context * ctx = whisper_init_from_file_with_params(params.model.c_str(), cparams);
2022-09-25 20:23:15 +02:00
if (ctx == nullptr) {
fprintf(stderr, "error: failed to initialize whisper context\n");
return 3;
}
// initialize openvino encoder. this has no effect on whisper.cpp builds that don't have OpenVINO configured
whisper_ctx_init_openvino_encoder(ctx, nullptr, params.openvino_encode_device.c_str(), nullptr);
for (int f = 0; f < (int) params.fname_inp.size(); ++f) {
const auto fname_inp = params.fname_inp[f];
const auto fname_out = f < (int) params.fname_out.size() && !params.fname_out[f].empty() ? params.fname_out[f] : params.fname_inp[f];
std::vector<float> pcmf32; // mono-channel F32 PCM
std::vector<std::vector<float>> pcmf32s; // stereo-channel F32 PCM
if (!::read_wav(fname_inp, pcmf32, pcmf32s, params.diarize)) {
fprintf(stderr, "error: failed to read WAV file '%s'\n", fname_inp.c_str());
continue;
2022-09-25 20:23:15 +02:00
}
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__);
}
}
if (params.detect_language) {
params.language = "auto";
}
if (!params.no_prints) {
// print system information
2022-10-27 16:22:10 +02:00
fprintf(stderr, "\n");
2022-10-29 11:26:03 +02:00
fprintf(stderr, "system_info: n_threads = %d / %d | %s\n",
params.n_threads*params.n_processors, std::thread::hardware_concurrency(), whisper_print_system_info());
2022-10-27 16:22:10 +02:00
// print some info about the processing
fprintf(stderr, "\n");
fprintf(stderr, "%s: processing '%s' (%d samples, %.1f sec), %d threads, %d processors, %d beams + best of %d, lang = %s, task = %s, %stimestamps = %d ...\n",
2022-10-29 11:26:03 +02:00
__func__, fname_inp.c_str(), int(pcmf32.size()), float(pcmf32.size())/WHISPER_SAMPLE_RATE,
params.n_threads, params.n_processors, params.beam_size, params.best_of,
params.language.c_str(),
params.translate ? "translate" : "transcribe",
params.tinydiarize ? "tdrz = 1, " : "",
params.no_timestamps ? 0 : 1);
fprintf(stderr, "\n");
}
// run the inference
{
whisper_full_params wparams = whisper_full_default_params(WHISPER_SAMPLING_GREEDY);
wparams.strategy = params.beam_size > 1 ? WHISPER_SAMPLING_BEAM_SEARCH : WHISPER_SAMPLING_GREEDY;
2022-11-25 18:08:51 +01:00
wparams.print_realtime = false;
wparams.print_progress = params.print_progress;
2022-11-25 18:08:51 +01:00
wparams.print_timestamps = !params.no_timestamps;
wparams.print_special = params.print_special;
wparams.translate = params.translate;
wparams.language = params.language.c_str();
wparams.detect_language = params.detect_language;
2022-11-25 18:08:51 +01:00
wparams.n_threads = params.n_threads;
wparams.n_max_text_ctx = params.max_context >= 0 ? params.max_context : wparams.n_max_text_ctx;
wparams.offset_ms = params.offset_t_ms;
wparams.duration_ms = params.duration_ms;
wparams.token_timestamps = params.output_wts || params.output_jsn_full || params.max_len > 0;
2022-11-25 18:08:51 +01:00
wparams.thold_pt = params.word_thold;
wparams.max_len = params.output_wts && params.max_len == 0 ? 60 : params.max_len;
wparams.split_on_word = params.split_on_word;
wparams.audio_ctx = params.audio_ctx;
2022-11-25 18:08:51 +01:00
wparams.speed_up = params.speed_up;
whisper : significantly improve the inference quality (#1148) * Fix MSVC compile error C3688 Instead of simply using 'add_compile_options(/utf-8)' to address the MSVC compile error C3688, a better approach would be to handle it in a way that prevents passing '/utf-8' to NVCC. * Significantly improve inference quality In the function `log_mel_spectrogram_worker_thread`, there's an array out-of-bounds issue occurring during the calculation of complex number moduli. This issue is causing disruptions in the FFT spectrum, which, in turn, is reducing the quality of inference. * Significantly improve inference quality At last, I've pinpointed the actual source of the problem. Given that the frequency spectrum generated from real input data is symmetrical around the Nyquist frequency, there's a for-loop within the `log_mel_spectrogram_worker_thread` function that attempts to fold the frequency spectrum. Regrettably, a bug within this for-loop is causing a frame shift in the frequency spectrum. The previous attempt to remedy this, which involved using `fft_size + 1` when calculating the modulus, was merely a band-aid solution and did not address the underlying issue. * Addressed a few minor issues Fixed the issue of `fft_out` continuously expanding. Resolved the fallback caused by using 'break' instead of `fft_in[j] = 0`. * Significantly improve inference quality Thanks for your patience everyone. It's finally sorted out. Now, the right side of the FFT spectrum is being flipped over to the left, and the amplitudes at corresponding positions on the left and right are added together (the spectrum on the left needs to be shifted by one position), then the average is calculated. FFT_OUT[0] is no longer discarded, making full use of the limited space to pack in more information. * Add annotation and performance improvement * Calculate FFT only when fft_in are not all zero * Some minor performance improvement * Fixed a bug impacting inference quality * The first version after all the analysis is completed. * Fix some bugs and add debug mode * Fixed several bugs * Temporarily disable speed-up mode and add debug mode. * Add debug mode * Disable speed-up mode and add debug mode * Fix CI error (#1) * Fix error * Fix error * Fixed several bugs including [BLANK_AUDIO] problem * Remove Hard-coded hann window * Some Final Fix (#2) * Fix error * Fix error * Probably the last commit * Probably the last commit * whisper : minor coding style changes * whisper : remove debug from public API --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-08-27 18:51:33 +02:00
wparams.debug_mode = params.debug_mode;
wparams.tdrz_enable = params.tinydiarize; // [TDRZ]
wparams.initial_prompt = params.prompt.c_str();
wparams.greedy.best_of = params.best_of;
wparams.beam_search.beam_size = params.beam_size;
wparams.temperature_inc = params.no_fallback ? 0.0f : wparams.temperature_inc;
wparams.entropy_thold = params.entropy_thold;
wparams.logprob_thold = params.logprob_thold;
wparams.no_timestamps = params.no_timestamps;
whisper_print_user_data user_data = { &params, &pcmf32s, 0 };
// 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 = &user_data;
}
if (wparams.print_progress) {
wparams.progress_callback = whisper_print_progress_callback;
wparams.progress_callback_user_data = &user_data;
}
// examples for abort mechanism
// in examples below, we do not abort the processing, but we could if the flag is set to true
// the callback is called before every encoder run - if it returns false, the processing is aborted
{
static bool is_aborted = false; // NOTE: this should be atomic to avoid data race
wparams.encoder_begin_callback = [](struct whisper_context * /*ctx*/, struct whisper_state * /*state*/, void * user_data) {
bool is_aborted = *(bool*)user_data;
return !is_aborted;
};
wparams.encoder_begin_callback_user_data = &is_aborted;
}
// the callback is called before every computation - if it returns true, the computation is aborted
{
static bool is_aborted = false; // NOTE: this should be atomic to avoid data race
wparams.abort_callback = [](void * user_data) {
bool is_aborted = *(bool*)user_data;
return is_aborted;
};
wparams.abort_callback_user_data = &is_aborted;
}
2022-10-29 11:26:03 +02:00
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 10;
}
}
2022-09-25 20:23:15 +02:00
// output stuff
{
printf("\n");
// output to text file
if (params.output_txt) {
const auto fname_txt = fname_out + ".txt";
output_txt(ctx, fname_txt.c_str(), params, pcmf32s);
}
// output to VTT file
if (params.output_vtt) {
const auto fname_vtt = fname_out + ".vtt";
output_vtt(ctx, fname_vtt.c_str(), params, pcmf32s);
}
// output to SRT file
if (params.output_srt) {
const auto fname_srt = fname_out + ".srt";
output_srt(ctx, fname_srt.c_str(), params, pcmf32s);
}
// output to WTS file
if (params.output_wts) {
const auto fname_wts = fname_out + ".wts";
output_wts(ctx, fname_wts.c_str(), fname_inp.c_str(), params, float(pcmf32.size() + 1000)/WHISPER_SAMPLE_RATE, pcmf32s);
}
// output to CSV file
if (params.output_csv) {
const auto fname_csv = fname_out + ".csv";
output_csv(ctx, fname_csv.c_str(), params, pcmf32s);
}
// output to JSON file
if (params.output_jsn) {
const auto fname_jsn = fname_out + ".json";
output_json(ctx, fname_jsn.c_str(), params, pcmf32s, params.output_jsn_full);
}
// output to LRC file
if (params.output_lrc) {
const auto fname_lrc = fname_out + ".lrc";
output_lrc(ctx, fname_lrc.c_str(), params, pcmf32s);
}
// output to score file
if (params.log_score) {
const auto fname_score = fname_out + ".score.txt";
output_score(ctx, fname_score.c_str(), params, pcmf32s);
}
}
2022-09-25 20:23:15 +02:00
}
whisper_print_timings(ctx);
whisper_free(ctx);
2022-09-25 20:23:15 +02:00
return 0;
}