spark 网站开发,wordpress 设h1,怎么介绍自己做的电影网站,一般做兼职在哪个网站whisper.cpp是一个C编写的轻量级开源智能语音识别库#xff0c;是基于openai的开源python智能语音模型whisper的移植版本#xff0c;依赖项少#xff0c;内存占用低#xff0c;性能更优#xff0c;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.c…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 yetproject(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 SRCsrc/*.hsrc/*.cpp
)add_executable(${PROJECT_NAME} ${SRC})target_link_libraries(${PROJECT_NAME}commonwhisper # 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::vectorstd::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 stringstd::string tdrz_speaker_turn [SPEAKER_TURN]; // TODO: set from command linestd::string openvino_encode_device CPU;std::vectorstd::string fname_inp {};std::vectorstd::string fname_out {};
};struct whisper_print_user_data
{const whisper_params* params;const std::vectorstd::vectorfloat* pcmf32s;int progress_prev;
};std::string estimate_diarization_speaker(std::vectorstd::vectorfloat 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 segmentsconst 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 lineif (!params.no_timestamps || params.diarize){printf(\n);}fflush(stdout);}
}bool output_txt(struct whisper_context* ctx, const char* fname, const whisper_params params, std::vectorstd::vectorfloat 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 paramswhisper_params params;params.model model_file_path;params.fname_inp.emplace_back(audio_file_path);// whisper initstruct 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 dont have OpenVINO configuredwhisper_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::vectorfloat pcmf32; // mono-channel F32 PCMstd::vectorstd::vectorfloat pcmf32s; // stereo-channel F32 PCMif (!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 segmentif (!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 racewparams.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 racewparams.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 fileif (params.output_txt){const auto fname_txt fname_out .txt;output_txt(ctx, fname_txt.c_str(), params, pcmf32s);}}}// whisper releasewhisper_print_timings(ctx);whisper_free(ctx);return 0;
}
注
whisper支持的模型文件需要自己去下载whisper.cpp编译可以配置多种类型的增强选项比如支持CPU/GPU加速数据计算加速库whisper.cpp的编译cmake文件做了少量改动方便集成到项目具体可参看demo
源码
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