/** * Copyright FunASR (https://github.com/alibaba-damo-academy/FunASR). All Rights Reserved. * MIT License (https://opensource.org/licenses/MIT) */ #ifndef _WIN32 #include #else #include #endif #include #include #include #include #include #include #include #include #include "util.h" #include "funasrruntime.h" #include "tclap/CmdLine.h" #include "com-define.h" #include "audio.h" using namespace std; std::atomic wav_index(0); std::mutex mtx; bool is_target_file(const std::string& filename, const std::string target) { std::size_t pos = filename.find_last_of("."); if (pos == std::string::npos) { return false; } std::string extension = filename.substr(pos + 1); return (extension == target); } void GetValue(TCLAP::ValueArg& value_arg, string key, std::map& model_path) { model_path.insert({key, value_arg.getValue()}); LOG(INFO)<< key << " : " << value_arg.getValue(); } void runReg(FUNASR_HANDLE tpass_handle, std::vector chunk_size, vector wav_list, vector wav_ids, int audio_fs, float* total_length, long* total_time, int core_id, ASR_TYPE asr_mode_, string nn_hotwords_, float glob_beam, float lat_beam, float am_scale, int inc_bias, unordered_map hws_map) { struct timeval start, end; long seconds = 0; float n_total_length = 0.0f; long n_total_time = 0; FUNASR_DEC_HANDLE decoder_handle = FunASRWfstDecoderInit(tpass_handle, ASR_TWO_PASS, glob_beam, lat_beam, am_scale); // load hotwords list and build graph FunWfstDecoderLoadHwsRes(decoder_handle, inc_bias, hws_map); std::vector> hotwords_embedding = CompileHotwordEmbedding(tpass_handle, nn_hotwords_, ASR_TWO_PASS); // init online features FUNASR_HANDLE tpass_online_handle=FunTpassOnlineInit(tpass_handle, chunk_size); // warm up for (size_t i = 0; i < 2; i++) { int32_t sampling_rate_ = audio_fs; funasr::Audio audio(1); if(is_target_file(wav_list[0].c_str(), "wav")){ if(!audio.LoadWav2Char(wav_list[0].c_str(), &sampling_rate_)){ LOG(ERROR)<<"Failed to load "<< wav_list[0]; exit(-1); } }else if(is_target_file(wav_list[0].c_str(), "pcm")){ if (!audio.LoadPcmwav2Char(wav_list[0].c_str(), &sampling_rate_)){ LOG(ERROR)<<"Failed to load "<< wav_list[0]; exit(-1); } }else{ if (!audio.FfmpegLoad(wav_list[0].c_str(), true)){ LOG(ERROR)<<"Failed to load "<< wav_list[0]; exit(-1); } } char* speech_buff = audio.GetSpeechChar(); int buff_len = audio.GetSpeechLen()*2; int step = 1600*2; bool is_final = false; std::vector> punc_cache(2); for (int sample_offset = 0; sample_offset < buff_len; sample_offset += std::min(step, buff_len - sample_offset)) { if (sample_offset + step >= buff_len - 1) { step = buff_len - sample_offset; is_final = true; } else { is_final = false; } FUNASR_RESULT result = FunTpassInferBuffer(tpass_handle, tpass_online_handle, speech_buff+sample_offset, step, punc_cache, is_final, sampling_rate_, "pcm", (ASR_TYPE)asr_mode_, hotwords_embedding, true, decoder_handle); if (result) { FunASRFreeResult(result); } } } while (true) { // 使用原子变量获取索引并递增 int i = wav_index.fetch_add(1); if (i >= wav_list.size()) { break; } int32_t sampling_rate_ = audio_fs; funasr::Audio audio(1); if(is_target_file(wav_list[i].c_str(), "wav")){ if(!audio.LoadWav2Char(wav_list[i].c_str(), &sampling_rate_)){ LOG(ERROR)<<"Failed to load "<< wav_list[i]; exit(-1); } }else if(is_target_file(wav_list[i].c_str(), "pcm")){ if (!audio.LoadPcmwav2Char(wav_list[i].c_str(), &sampling_rate_)){ LOG(ERROR)<<"Failed to load "<< wav_list[i]; exit(-1); } }else{ if (!audio.FfmpegLoad(wav_list[i].c_str(), true)){ LOG(ERROR)<<"Failed to load "<< wav_list[i]; exit(-1); } } char* speech_buff = audio.GetSpeechChar(); int buff_len = audio.GetSpeechLen()*2; int step = 1600*2; bool is_final = false; string online_res=""; string tpass_res=""; string time_stamp_res=""; std::vector> punc_cache(2); for (int sample_offset = 0; sample_offset < buff_len; sample_offset += std::min(step, buff_len - sample_offset)) { if (sample_offset + step >= buff_len - 1) { step = buff_len - sample_offset; is_final = true; } else { is_final = false; } gettimeofday(&start, nullptr); FUNASR_RESULT result = FunTpassInferBuffer(tpass_handle, tpass_online_handle, speech_buff+sample_offset, step, punc_cache, is_final, sampling_rate_, "pcm", (ASR_TYPE)asr_mode_, hotwords_embedding, true, decoder_handle); gettimeofday(&end, nullptr); seconds = (end.tv_sec - start.tv_sec); long taking_micros = ((seconds * 1000000) + end.tv_usec) - (start.tv_usec); n_total_time += taking_micros; if (result) { string online_msg = FunASRGetResult(result, 0); online_res += online_msg; if(online_msg != ""){ LOG(INFO) <<"Thread: " << this_thread::get_id() <<" " << wav_ids[i] <<" : "< guard(mtx); *total_length += n_total_length; if(*total_time < n_total_time){ *total_time = n_total_time; } } FunWfstDecoderUnloadHwsRes(decoder_handle); FunASRWfstDecoderUninit(decoder_handle); FunTpassOnlineUninit(tpass_online_handle); } int main(int argc, char** argv) { google::InitGoogleLogging(argv[0]); FLAGS_logtostderr = true; TCLAP::CmdLine cmd("funasr-onnx-2pass", ' ', "1.0"); TCLAP::ValueArg offline_model_dir("", OFFLINE_MODEL_DIR, "the asr offline model path, which contains model.onnx, config.yaml, am.mvn", true, "", "string"); TCLAP::ValueArg online_model_dir("", ONLINE_MODEL_DIR, "the asr online model path, which contains model.onnx, decoder.onnx, config.yaml, am.mvn", true, "", "string"); TCLAP::ValueArg quantize("", QUANTIZE, "true (Default), load the model of model.onnx in model_dir. If set true, load the model of model_quant.onnx in model_dir", false, "true", "string"); TCLAP::ValueArg vad_dir("", VAD_DIR, "the vad online model path, which contains model.onnx, vad.yaml, vad.mvn", false, "", "string"); TCLAP::ValueArg vad_quant("", VAD_QUANT, "true (Default), load the model of model.onnx in vad_dir. If set true, load the model of model_quant.onnx in vad_dir", false, "true", "string"); TCLAP::ValueArg punc_dir("", PUNC_DIR, "the punc online model path, which contains model.onnx, punc.yaml", false, "", "string"); TCLAP::ValueArg punc_quant("", PUNC_QUANT, "true (Default), load the model of model.onnx in punc_dir. If set true, load the model of model_quant.onnx in punc_dir", false, "true", "string"); TCLAP::ValueArg itn_dir("", ITN_DIR, "the itn model(fst) path, which contains zh_itn_tagger.fst and zh_itn_verbalizer.fst", false, "", "string"); TCLAP::ValueArg lm_dir("", LM_DIR, "the lm model path, which contains compiled models: TLG.fst, config.yaml, lexicon.txt ", false, "", "string"); TCLAP::ValueArg global_beam("", GLOB_BEAM, "the decoding beam for beam searching ", false, 3.0, "float"); TCLAP::ValueArg lattice_beam("", LAT_BEAM, "the lattice generation beam for beam searching ", false, 3.0, "float"); TCLAP::ValueArg am_scale("", AM_SCALE, "the acoustic scale for beam searching ", false, 10.0, "float"); TCLAP::ValueArg fst_inc_wts("", FST_INC_WTS, "the fst hotwords incremental bias", false, 20, "int32_t"); TCLAP::ValueArg asr_mode("", ASR_MODE, "offline, online, 2pass", false, "2pass", "string"); TCLAP::ValueArg onnx_thread("", "model-thread-num", "onnxruntime SetIntraOpNumThreads", false, 1, "int32_t"); TCLAP::ValueArg thread_num_("", THREAD_NUM, "multi-thread num for rtf", false, 1, "int32_t"); TCLAP::ValueArg wav_path("", WAV_PATH, "the input could be: wav_path, e.g.: asr_example.wav; pcm_path, e.g.: asr_example.pcm; wav.scp, kaldi style wav list (wav_id \t wav_path)", true, "", "string"); TCLAP::ValueArg audio_fs("", AUDIO_FS, "the sample rate of audio", false, 16000, "int32_t"); TCLAP::ValueArg hotword("", HOTWORD, "the hotword file, one hotword perline, Format: Hotword Weight (could be: 阿里巴巴 20)", false, "", "string"); cmd.add(offline_model_dir); cmd.add(online_model_dir); cmd.add(quantize); cmd.add(vad_dir); cmd.add(vad_quant); cmd.add(punc_dir); cmd.add(punc_quant); cmd.add(itn_dir); cmd.add(lm_dir); cmd.add(global_beam); cmd.add(lattice_beam); cmd.add(am_scale); cmd.add(fst_inc_wts); cmd.add(wav_path); cmd.add(audio_fs); cmd.add(asr_mode); cmd.add(onnx_thread); cmd.add(thread_num_); cmd.add(hotword); cmd.parse(argc, argv); std::map model_path; GetValue(offline_model_dir, OFFLINE_MODEL_DIR, model_path); GetValue(online_model_dir, ONLINE_MODEL_DIR, model_path); GetValue(quantize, QUANTIZE, model_path); GetValue(vad_dir, VAD_DIR, model_path); GetValue(vad_quant, VAD_QUANT, model_path); GetValue(punc_dir, PUNC_DIR, model_path); GetValue(punc_quant, PUNC_QUANT, model_path); GetValue(itn_dir, ITN_DIR, model_path); GetValue(lm_dir, LM_DIR, model_path); GetValue(wav_path, WAV_PATH, model_path); GetValue(asr_mode, ASR_MODE, model_path); struct timeval start, end; gettimeofday(&start, nullptr); int thread_num = onnx_thread.getValue(); int asr_mode_ = -1; if(model_path[ASR_MODE] == "offline"){ asr_mode_ = 0; }else if(model_path[ASR_MODE] == "online"){ asr_mode_ = 1; }else if(model_path[ASR_MODE] == "2pass"){ asr_mode_ = 2; }else{ LOG(ERROR) << "Wrong asr-mode : " << model_path[ASR_MODE]; exit(-1); } FUNASR_HANDLE tpass_hanlde=FunTpassInit(model_path, thread_num); if (!tpass_hanlde) { LOG(ERROR) << "FunTpassInit init failed"; exit(-1); } float glob_beam = 3.0f; float lat_beam = 3.0f; float am_sc = 10.0f; if (lm_dir.isSet()) { glob_beam = global_beam.getValue(); lat_beam = lattice_beam.getValue(); am_sc = am_scale.getValue(); } gettimeofday(&end, nullptr); long seconds = (end.tv_sec - start.tv_sec); long modle_init_micros = ((seconds * 1000000) + end.tv_usec) - (start.tv_usec); LOG(INFO) << "Model initialization takes " << (double)modle_init_micros / 1000000 << " s"; // hotword file unordered_map hws_map; std::string nn_hotwords_ = ""; std::string hotword_path = hotword.getValue(); LOG(INFO) << "hotword path: " << hotword_path; funasr::ExtractHws(hotword_path, hws_map, nn_hotwords_); // read wav_path vector wav_list; vector wav_ids; string default_id = "wav_default_id"; string wav_path_ = model_path.at(WAV_PATH); if(is_target_file(wav_path_, "scp")){ ifstream in(wav_path_); if (!in.is_open()) { LOG(ERROR) << "Failed to open file: " << model_path.at(WAV_SCP) ; return 0; } string line; while(getline(in, line)) { istringstream iss(line); string column1, column2; iss >> column1 >> column2; wav_list.emplace_back(column2); wav_ids.emplace_back(column1); } in.close(); }else{ wav_list.emplace_back(wav_path_); wav_ids.emplace_back(default_id); } std::vector chunk_size = {5,10,5}; // 多线程测试 float total_length = 0.0f; long total_time = 0; std::vector threads; int rtf_threds = thread_num_.getValue(); for (int i = 0; i < rtf_threds; i++) { threads.emplace_back(thread(runReg, tpass_hanlde, chunk_size, wav_list, wav_ids, audio_fs.getValue(), &total_length, &total_time, i, (ASR_TYPE)asr_mode_, nn_hotwords_, glob_beam, lat_beam, am_sc, fst_inc_wts.getValue(), hws_map)); } for (auto& thread : threads) { thread.join(); } LOG(INFO) << "total_time_wav " << (long)(total_length * 1000) << " ms"; LOG(INFO) << "total_time_comput " << total_time / 1000 << " ms"; LOG(INFO) << "total_rtf " << (double)total_time/ (total_length*1000000); LOG(INFO) << "speedup " << 1.0/((double)total_time/ (total_length*1000000)); FunTpassUninit(tpass_hanlde); return 0; }