mirror of
https://github.com/ggerganov/whisper.cpp.git
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e30c679928
* scripts : update sync [no ci] * files : reorganize [no ci] * sync : llama.cpp * cmake : link math library * cmake : build normal ggml library * files : move headers to include * objc : fix path to ggml-metal.h * ci : fix WHISPER_CUDA -> GGML_CUDA * scripts : sync LICENSE [no ci]
421 lines
17 KiB
C++
421 lines
17 KiB
C++
// Real-time speech recognition of input from a microphone
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//
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// A very quick-n-dirty implementation serving mainly as a proof of concept.
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//
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#include "common-sdl.h"
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#include "common.h"
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#include "whisper.h"
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#include <cassert>
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#include <cstdio>
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#include <string>
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#include <thread>
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#include <vector>
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#include <fstream>
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// command-line parameters
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struct whisper_params {
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int32_t n_threads = std::min(4, (int32_t) std::thread::hardware_concurrency());
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int32_t step_ms = 3000;
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int32_t length_ms = 10000;
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int32_t keep_ms = 200;
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int32_t capture_id = -1;
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int32_t max_tokens = 32;
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int32_t audio_ctx = 0;
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float vad_thold = 0.6f;
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float freq_thold = 100.0f;
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bool translate = false;
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bool no_fallback = false;
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bool print_special = false;
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bool no_context = true;
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bool no_timestamps = false;
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bool tinydiarize = false;
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bool save_audio = false; // save audio to wav file
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bool use_gpu = true;
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bool flash_attn = false;
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std::string language = "en";
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std::string model = "models/ggml-base.en.bin";
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std::string fname_out;
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};
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void whisper_print_usage(int argc, char ** argv, const whisper_params & params);
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static bool whisper_params_parse(int argc, char ** argv, whisper_params & params) {
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for (int i = 1; i < argc; i++) {
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std::string arg = argv[i];
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if (arg == "-h" || arg == "--help") {
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whisper_print_usage(argc, argv, params);
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exit(0);
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}
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else if (arg == "-t" || arg == "--threads") { params.n_threads = std::stoi(argv[++i]); }
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else if ( arg == "--step") { params.step_ms = std::stoi(argv[++i]); }
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else if ( arg == "--length") { params.length_ms = std::stoi(argv[++i]); }
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else if ( arg == "--keep") { params.keep_ms = std::stoi(argv[++i]); }
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else if (arg == "-c" || arg == "--capture") { params.capture_id = std::stoi(argv[++i]); }
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else if (arg == "-mt" || arg == "--max-tokens") { params.max_tokens = std::stoi(argv[++i]); }
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else if (arg == "-ac" || arg == "--audio-ctx") { params.audio_ctx = std::stoi(argv[++i]); }
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else if (arg == "-vth" || arg == "--vad-thold") { params.vad_thold = std::stof(argv[++i]); }
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else if (arg == "-fth" || arg == "--freq-thold") { params.freq_thold = std::stof(argv[++i]); }
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else if (arg == "-tr" || arg == "--translate") { params.translate = true; }
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else if (arg == "-nf" || arg == "--no-fallback") { params.no_fallback = true; }
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else if (arg == "-ps" || arg == "--print-special") { params.print_special = true; }
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else if (arg == "-kc" || arg == "--keep-context") { params.no_context = false; }
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else if (arg == "-l" || arg == "--language") { params.language = argv[++i]; }
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else if (arg == "-m" || arg == "--model") { params.model = argv[++i]; }
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else if (arg == "-f" || arg == "--file") { params.fname_out = argv[++i]; }
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else if (arg == "-tdrz" || arg == "--tinydiarize") { params.tinydiarize = true; }
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else if (arg == "-sa" || arg == "--save-audio") { params.save_audio = true; }
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else if (arg == "-ng" || arg == "--no-gpu") { params.use_gpu = false; }
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else if (arg == "-fa" || arg == "--flash-attn") { params.flash_attn = true; }
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else {
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fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
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whisper_print_usage(argc, argv, params);
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exit(0);
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}
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}
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return true;
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}
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void whisper_print_usage(int /*argc*/, char ** argv, const whisper_params & params) {
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fprintf(stderr, "\n");
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fprintf(stderr, "usage: %s [options]\n", argv[0]);
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fprintf(stderr, "\n");
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fprintf(stderr, "options:\n");
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fprintf(stderr, " -h, --help [default] show this help message and exit\n");
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fprintf(stderr, " -t N, --threads N [%-7d] number of threads to use during computation\n", params.n_threads);
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fprintf(stderr, " --step N [%-7d] audio step size in milliseconds\n", params.step_ms);
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fprintf(stderr, " --length N [%-7d] audio length in milliseconds\n", params.length_ms);
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fprintf(stderr, " --keep N [%-7d] audio to keep from previous step in ms\n", params.keep_ms);
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fprintf(stderr, " -c ID, --capture ID [%-7d] capture device ID\n", params.capture_id);
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fprintf(stderr, " -mt N, --max-tokens N [%-7d] maximum number of tokens per audio chunk\n", params.max_tokens);
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fprintf(stderr, " -ac N, --audio-ctx N [%-7d] audio context size (0 - all)\n", params.audio_ctx);
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fprintf(stderr, " -vth N, --vad-thold N [%-7.2f] voice activity detection threshold\n", params.vad_thold);
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fprintf(stderr, " -fth N, --freq-thold N [%-7.2f] high-pass frequency cutoff\n", params.freq_thold);
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fprintf(stderr, " -tr, --translate [%-7s] translate from source language to english\n", params.translate ? "true" : "false");
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fprintf(stderr, " -nf, --no-fallback [%-7s] do not use temperature fallback while decoding\n", params.no_fallback ? "true" : "false");
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fprintf(stderr, " -ps, --print-special [%-7s] print special tokens\n", params.print_special ? "true" : "false");
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fprintf(stderr, " -kc, --keep-context [%-7s] keep context between audio chunks\n", params.no_context ? "false" : "true");
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fprintf(stderr, " -l LANG, --language LANG [%-7s] spoken language\n", params.language.c_str());
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fprintf(stderr, " -m FNAME, --model FNAME [%-7s] model path\n", params.model.c_str());
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fprintf(stderr, " -f FNAME, --file FNAME [%-7s] text output file name\n", params.fname_out.c_str());
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fprintf(stderr, " -tdrz, --tinydiarize [%-7s] enable tinydiarize (requires a tdrz model)\n", params.tinydiarize ? "true" : "false");
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fprintf(stderr, " -sa, --save-audio [%-7s] save the recorded audio to a file\n", params.save_audio ? "true" : "false");
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fprintf(stderr, " -ng, --no-gpu [%-7s] disable GPU inference\n", params.use_gpu ? "false" : "true");
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fprintf(stderr, " -fa, --flash-attn [%-7s] flash attention during inference\n", params.flash_attn ? "true" : "false");
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fprintf(stderr, "\n");
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}
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int main(int argc, char ** argv) {
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whisper_params params;
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if (whisper_params_parse(argc, argv, params) == false) {
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return 1;
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}
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params.keep_ms = std::min(params.keep_ms, params.step_ms);
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params.length_ms = std::max(params.length_ms, params.step_ms);
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const int n_samples_step = (1e-3*params.step_ms )*WHISPER_SAMPLE_RATE;
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const int n_samples_len = (1e-3*params.length_ms)*WHISPER_SAMPLE_RATE;
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const int n_samples_keep = (1e-3*params.keep_ms )*WHISPER_SAMPLE_RATE;
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const int n_samples_30s = (1e-3*30000.0 )*WHISPER_SAMPLE_RATE;
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const bool use_vad = n_samples_step <= 0; // sliding window mode uses VAD
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const int n_new_line = !use_vad ? std::max(1, params.length_ms / params.step_ms - 1) : 1; // number of steps to print new line
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params.no_timestamps = !use_vad;
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params.no_context |= use_vad;
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params.max_tokens = 0;
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// init audio
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audio_async audio(params.length_ms);
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if (!audio.init(params.capture_id, WHISPER_SAMPLE_RATE)) {
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fprintf(stderr, "%s: audio.init() failed!\n", __func__);
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return 1;
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}
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audio.resume();
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// whisper init
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if (params.language != "auto" && whisper_lang_id(params.language.c_str()) == -1){
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fprintf(stderr, "error: unknown language '%s'\n", params.language.c_str());
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whisper_print_usage(argc, argv, params);
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exit(0);
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}
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struct whisper_context_params cparams = whisper_context_default_params();
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cparams.use_gpu = params.use_gpu;
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cparams.flash_attn = params.flash_attn;
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struct whisper_context * ctx = whisper_init_from_file_with_params(params.model.c_str(), cparams);
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std::vector<float> pcmf32 (n_samples_30s, 0.0f);
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std::vector<float> pcmf32_old;
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std::vector<float> pcmf32_new(n_samples_30s, 0.0f);
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std::vector<whisper_token> prompt_tokens;
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// print some info about the processing
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{
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fprintf(stderr, "\n");
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if (!whisper_is_multilingual(ctx)) {
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if (params.language != "en" || params.translate) {
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params.language = "en";
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params.translate = false;
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fprintf(stderr, "%s: WARNING: model is not multilingual, ignoring language and translation options\n", __func__);
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}
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}
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fprintf(stderr, "%s: processing %d samples (step = %.1f sec / len = %.1f sec / keep = %.1f sec), %d threads, lang = %s, task = %s, timestamps = %d ...\n",
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__func__,
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n_samples_step,
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float(n_samples_step)/WHISPER_SAMPLE_RATE,
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float(n_samples_len )/WHISPER_SAMPLE_RATE,
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float(n_samples_keep)/WHISPER_SAMPLE_RATE,
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params.n_threads,
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params.language.c_str(),
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params.translate ? "translate" : "transcribe",
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params.no_timestamps ? 0 : 1);
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if (!use_vad) {
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fprintf(stderr, "%s: n_new_line = %d, no_context = %d\n", __func__, n_new_line, params.no_context);
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} else {
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fprintf(stderr, "%s: using VAD, will transcribe on speech activity\n", __func__);
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}
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fprintf(stderr, "\n");
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}
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int n_iter = 0;
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bool is_running = true;
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std::ofstream fout;
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if (params.fname_out.length() > 0) {
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fout.open(params.fname_out);
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if (!fout.is_open()) {
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fprintf(stderr, "%s: failed to open output file '%s'!\n", __func__, params.fname_out.c_str());
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return 1;
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}
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}
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wav_writer wavWriter;
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// save wav file
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if (params.save_audio) {
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// Get current date/time for filename
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time_t now = time(0);
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char buffer[80];
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strftime(buffer, sizeof(buffer), "%Y%m%d%H%M%S", localtime(&now));
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std::string filename = std::string(buffer) + ".wav";
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wavWriter.open(filename, WHISPER_SAMPLE_RATE, 16, 1);
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}
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printf("[Start speaking]\n");
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fflush(stdout);
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auto t_last = std::chrono::high_resolution_clock::now();
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const auto t_start = t_last;
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// main audio loop
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while (is_running) {
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if (params.save_audio) {
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wavWriter.write(pcmf32_new.data(), pcmf32_new.size());
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}
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// handle Ctrl + C
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is_running = sdl_poll_events();
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if (!is_running) {
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break;
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}
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// process new audio
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if (!use_vad) {
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while (true) {
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audio.get(params.step_ms, pcmf32_new);
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if ((int) pcmf32_new.size() > 2*n_samples_step) {
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fprintf(stderr, "\n\n%s: WARNING: cannot process audio fast enough, dropping audio ...\n\n", __func__);
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audio.clear();
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continue;
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}
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if ((int) pcmf32_new.size() >= n_samples_step) {
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audio.clear();
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break;
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}
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std::this_thread::sleep_for(std::chrono::milliseconds(1));
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}
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const int n_samples_new = pcmf32_new.size();
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// take up to params.length_ms audio from previous iteration
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const int n_samples_take = std::min((int) pcmf32_old.size(), std::max(0, n_samples_keep + n_samples_len - n_samples_new));
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//printf("processing: take = %d, new = %d, old = %d\n", n_samples_take, n_samples_new, (int) pcmf32_old.size());
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pcmf32.resize(n_samples_new + n_samples_take);
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for (int i = 0; i < n_samples_take; i++) {
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pcmf32[i] = pcmf32_old[pcmf32_old.size() - n_samples_take + i];
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}
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memcpy(pcmf32.data() + n_samples_take, pcmf32_new.data(), n_samples_new*sizeof(float));
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pcmf32_old = pcmf32;
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} else {
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const auto t_now = std::chrono::high_resolution_clock::now();
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const auto t_diff = std::chrono::duration_cast<std::chrono::milliseconds>(t_now - t_last).count();
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if (t_diff < 2000) {
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std::this_thread::sleep_for(std::chrono::milliseconds(100));
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continue;
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}
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audio.get(2000, pcmf32_new);
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if (::vad_simple(pcmf32_new, WHISPER_SAMPLE_RATE, 1000, params.vad_thold, params.freq_thold, false)) {
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audio.get(params.length_ms, pcmf32);
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} else {
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std::this_thread::sleep_for(std::chrono::milliseconds(100));
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continue;
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}
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t_last = t_now;
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}
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// run the inference
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{
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whisper_full_params wparams = whisper_full_default_params(WHISPER_SAMPLING_GREEDY);
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wparams.print_progress = false;
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wparams.print_special = params.print_special;
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wparams.print_realtime = false;
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wparams.print_timestamps = !params.no_timestamps;
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wparams.translate = params.translate;
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wparams.single_segment = !use_vad;
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wparams.max_tokens = params.max_tokens;
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wparams.language = params.language.c_str();
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wparams.n_threads = params.n_threads;
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wparams.audio_ctx = params.audio_ctx;
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wparams.tdrz_enable = params.tinydiarize; // [TDRZ]
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// disable temperature fallback
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//wparams.temperature_inc = -1.0f;
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wparams.temperature_inc = params.no_fallback ? 0.0f : wparams.temperature_inc;
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wparams.prompt_tokens = params.no_context ? nullptr : prompt_tokens.data();
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wparams.prompt_n_tokens = params.no_context ? 0 : prompt_tokens.size();
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if (whisper_full(ctx, wparams, pcmf32.data(), pcmf32.size()) != 0) {
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fprintf(stderr, "%s: failed to process audio\n", argv[0]);
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return 6;
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}
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// print result;
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{
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if (!use_vad) {
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printf("\33[2K\r");
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// print long empty line to clear the previous line
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printf("%s", std::string(100, ' ').c_str());
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printf("\33[2K\r");
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} else {
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const int64_t t1 = (t_last - t_start).count()/1000000;
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const int64_t t0 = std::max(0.0, t1 - pcmf32.size()*1000.0/WHISPER_SAMPLE_RATE);
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printf("\n");
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printf("### Transcription %d START | t0 = %d ms | t1 = %d ms\n", n_iter, (int) t0, (int) t1);
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printf("\n");
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}
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const int n_segments = whisper_full_n_segments(ctx);
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for (int i = 0; i < n_segments; ++i) {
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const char * text = whisper_full_get_segment_text(ctx, i);
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if (params.no_timestamps) {
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printf("%s", text);
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fflush(stdout);
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if (params.fname_out.length() > 0) {
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fout << text;
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}
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} else {
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const int64_t t0 = whisper_full_get_segment_t0(ctx, i);
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const int64_t t1 = whisper_full_get_segment_t1(ctx, i);
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std::string output = "[" + to_timestamp(t0, false) + " --> " + to_timestamp(t1, false) + "] " + text;
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if (whisper_full_get_segment_speaker_turn_next(ctx, i)) {
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output += " [SPEAKER_TURN]";
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}
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output += "\n";
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printf("%s", output.c_str());
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fflush(stdout);
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if (params.fname_out.length() > 0) {
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fout << output;
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}
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}
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}
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if (params.fname_out.length() > 0) {
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fout << std::endl;
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}
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if (use_vad) {
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printf("\n");
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printf("### Transcription %d END\n", n_iter);
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}
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}
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++n_iter;
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if (!use_vad && (n_iter % n_new_line) == 0) {
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printf("\n");
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// keep part of the audio for next iteration to try to mitigate word boundary issues
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pcmf32_old = std::vector<float>(pcmf32.end() - n_samples_keep, pcmf32.end());
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// Add tokens of the last full length segment as the prompt
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if (!params.no_context) {
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prompt_tokens.clear();
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const int n_segments = whisper_full_n_segments(ctx);
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for (int i = 0; i < n_segments; ++i) {
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const int token_count = whisper_full_n_tokens(ctx, i);
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for (int j = 0; j < token_count; ++j) {
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prompt_tokens.push_back(whisper_full_get_token_id(ctx, i, j));
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}
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}
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}
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}
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fflush(stdout);
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}
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}
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audio.pause();
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whisper_print_timings(ctx);
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whisper_free(ctx);
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return 0;
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}
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