开源C++智能语音识别库whisper.cpp开发使用入门

whisper.cpp是一个C++编写的轻量级开源智能语音识别库，是基于openai的开源python智能语音模型whisper的移植版本，依赖项少，内存占用低，性能更优，方便作为依赖库集成的到应用程序中提供语音识别功能。

以下基于whisper.cpp的源码利用C++ api来开发实例demo演示读取本地音频文件并转成文字。

项目结构

whispercpp_starter - whisper.cpp-v1.5.0 - src |- main.cpp - CMakeLists.txt

CMakeLists.txt

cmake_minimum_required(VERSION 3.15) # this only works for unix, xapian source code not support compile in windows yet project(whispercpp_starter) set(CMAKE_CXX_STANDARD 14) set(CMAKE_CXX_STANDARD_REQUIRED ON) add_subdirectory(whisper.cpp-v1.5.0) include_directories( ${CMAKE_CURRENT_SOURCE_DIR}/whisper.cpp-v1.5.0 ${CMAKE_CURRENT_SOURCE_DIR}/whisper.cpp-v1.5.0/examples ) file(GLOB SRC src/*.h src/*.cpp ) add_executable(${PROJECT_NAME} ${SRC}) target_link_libraries(${PROJECT_NAME} common whisper # remember to copy dll or so to bin folder )

main.cpp

#include <cmath> #include <fstream> #include <cstdio> #include <string> #include <thread> #include <vector> #include <cstring> #include "common.h" #include "whisper.h" #if defined(_MSC_VER) #pragma warning(disable: 4244 4267) // possible loss of data #endif // Terminal color map. 10 colors grouped in ranges [0.0, 0.1, ..., 0.9] // Lowest is red, middle is yellow, highest is green. const std::vector<std::string> k_colors = { "\033[38;5;196m", "\033[38;5;202m", "\033[38;5;208m", "\033[38;5;214m", "\033[38;5;220m", "\033[38;5;226m", "\033[38;5;190m", "\033[38;5;154m", "\033[38;5;118m", "\033[38;5;82m", }; // 500 -> 00:05.000 // 6000 -> 01:00.000 std::string to_timestamp(int64_t t, bool comma = false) { int64_t msec = t * 10; int64_t hr = msec / (1000 * 60 * 60); msec = msec - hr * (1000 * 60 * 60); int64_t min = msec / (1000 * 60); msec = msec - min * (1000 * 60); int64_t sec = msec / 1000; msec = msec - sec * 1000; char buf[32]; snprintf(buf, sizeof(buf), "%02d:%02d:%02d%s%03d", (int)hr, (int)min, (int)sec, comma ? "," : ".", (int)msec); return std::string(buf); } int timestamp_to_sample(int64_t t, int n_samples) { return std::max(0, std::min((int)n_samples - 1, (int)((t * WHISPER_SAMPLE_RATE) / 100))); } // 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; float word_thold = 0.01f; float entropy_thold = 2.40f; float logprob_thold = -1.00f; bool speed_up = false; 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 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::vector<std::string> fname_inp = {}; std::vector<std::string> fname_out = {}; }; 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); const int64_t is1 = timestamp_to_sample(t1, n_samples); 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); } if (!params.no_timestamps) { printf("[%s --> %s] ", to_timestamp(t0).c_str(), to_timestamp(t1).c_str()); } 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) { 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"; } return true; } int main(int argc, char** argv) { const std::string model_file_path = "./ggml-base.en.bin"; const std::string audio_file_path = "sample.wav"; // should be wav 16bit format // set whisper params whisper_params params; params.model = model_file_path; params.fname_inp.emplace_back(audio_file_path); // whisper init struct whisper_context_params cparams; cparams.use_gpu = params.use_gpu; struct whisper_context* ctx = whisper_init_from_file_with_params(params.model.c_str(), cparams); 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; } // print system information { fprintf(stderr, "\n"); fprintf(stderr, "system_info: n_threads = %d / %d | %s\n", params.n_threads * params.n_processors, std::thread::hardware_concurrency(), whisper_print_system_info()); } // 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__); } } if (params.detect_language) { params.language = "auto"; } 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", __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; wparams.print_realtime = false; wparams.print_progress = params.print_progress; 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; 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; 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.speed_up = params.speed_up; 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; 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; } 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; } } // 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); } } } // whisper release whisper_print_timings(ctx); whisper_free(ctx); return 0; }

注：

源码

whispercpp_starter

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