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