| | |
| | | #include <fstream> |
| | | #include "precomp.h" |
| | | |
| | | void FsmnVad::InitVad(const std::string &vad_model, const std::string &vad_cmvn, int vad_sample_rate, int vad_silence_duration, int vad_max_len, |
| | | float vad_speech_noise_thres) { |
| | | void FsmnVad::InitVad(const std::string &vad_model, const std::string &vad_cmvn, const std::string &vad_config) { |
| | | session_options_.SetIntraOpNumThreads(1); |
| | | session_options_.SetGraphOptimizationLevel(ORT_ENABLE_ALL); |
| | | session_options_.DisableCpuMemArena(); |
| | | this->vad_sample_rate_ = vad_sample_rate; |
| | | this->vad_silence_duration_=vad_silence_duration; |
| | | this->vad_max_len_=vad_max_len; |
| | | this->vad_speech_noise_thres_=vad_speech_noise_thres; |
| | | |
| | | ReadModel(vad_model); |
| | | ReadModel(vad_model.c_str()); |
| | | LoadCmvn(vad_cmvn.c_str()); |
| | | LoadConfigFromYaml(vad_config.c_str()); |
| | | InitCache(); |
| | | |
| | | fbank_opts.frame_opts.dither = 0; |
| | | fbank_opts.mel_opts.num_bins = 80; |
| | | fbank_opts.frame_opts.samp_freq = vad_sample_rate; |
| | | fbank_opts.frame_opts.window_type = "hamming"; |
| | | fbank_opts.frame_opts.frame_shift_ms = 10; |
| | | fbank_opts.frame_opts.frame_length_ms = 25; |
| | | fbank_opts.energy_floor = 0; |
| | | fbank_opts.mel_opts.debug_mel = false; |
| | | |
| | | } |
| | | |
| | | void FsmnVad::ReadModel(const std::string &vad_model) { |
| | | void FsmnVad::LoadConfigFromYaml(const char* filename){ |
| | | |
| | | YAML::Node config; |
| | | try{ |
| | | config = YAML::LoadFile(filename); |
| | | }catch(exception const &e){ |
| | | LOG(ERROR) << "Error loading file, yaml file error or not exist."; |
| | | exit(-1); |
| | | } |
| | | |
| | | try{ |
| | | YAML::Node frontend_conf = config["frontend_conf"]; |
| | | YAML::Node post_conf = config["vad_post_conf"]; |
| | | |
| | | this->vad_sample_rate_ = frontend_conf["fs"].as<int>(); |
| | | this->vad_silence_duration_ = post_conf["max_end_silence_time"].as<int>(); |
| | | this->vad_max_len_ = post_conf["max_single_segment_time"].as<int>(); |
| | | this->vad_speech_noise_thres_ = post_conf["speech_noise_thres"].as<double>(); |
| | | |
| | | fbank_opts.frame_opts.dither = frontend_conf["dither"].as<float>(); |
| | | fbank_opts.mel_opts.num_bins = frontend_conf["n_mels"].as<int>(); |
| | | fbank_opts.frame_opts.samp_freq = (float)vad_sample_rate_; |
| | | fbank_opts.frame_opts.window_type = frontend_conf["window"].as<string>(); |
| | | fbank_opts.frame_opts.frame_shift_ms = frontend_conf["frame_shift"].as<float>(); |
| | | fbank_opts.frame_opts.frame_length_ms = frontend_conf["frame_length"].as<float>(); |
| | | fbank_opts.energy_floor = 0; |
| | | fbank_opts.mel_opts.debug_mel = false; |
| | | }catch(exception const &e){ |
| | | LOG(ERROR) << "Error when load argument from vad config YAML."; |
| | | exit(-1); |
| | | } |
| | | } |
| | | |
| | | void FsmnVad::ReadModel(const char* vad_model) { |
| | | try { |
| | | vad_session_ = std::make_shared<Ort::Session>( |
| | | env_, vad_model.c_str(), session_options_); |
| | | env_, vad_model, session_options_); |
| | | } catch (std::exception const &e) { |
| | | LOG(ERROR) << "Error when load vad onnx model: " << e.what(); |
| | | exit(0); |
| | | } |
| | | LOG(INFO) << "vad onnx:"; |
| | | GetInputOutputInfo(vad_session_, &vad_in_names_, &vad_out_names_); |
| | | } |
| | | |
| | |
| | | shape << j; |
| | | shape << " "; |
| | | } |
| | | LOG(INFO) << "\tInput " << i << " : name=" << name.get() << " type=" << type |
| | | << " dims=" << shape.str(); |
| | | // LOG(INFO) << "\tInput " << i << " : name=" << name.get() << " type=" << type |
| | | // << " dims=" << shape.str(); |
| | | (*in_names)[i] = name.get(); |
| | | name.release(); |
| | | } |
| | |
| | | shape << j; |
| | | shape << " "; |
| | | } |
| | | LOG(INFO) << "\tOutput " << i << " : name=" << name.get() << " type=" << type |
| | | << " dims=" << shape.str(); |
| | | // LOG(INFO) << "\tOutput " << i << " : name=" << name.get() << " type=" << type |
| | | // << " dims=" << shape.str(); |
| | | (*out_names)[i] = name.get(); |
| | | name.release(); |
| | | } |
| | |
| | | // 4. Onnx infer |
| | | std::vector<Ort::Value> vad_ort_outputs; |
| | | try { |
| | | VLOG(3) << "Start infer"; |
| | | vad_ort_outputs = vad_session_->Run( |
| | | Ort::RunOptions{nullptr}, vad_in_names_.data(), vad_inputs.data(), |
| | | vad_inputs.size(), vad_out_names_.data(), vad_out_names_.size()); |
| | | } catch (std::exception const &e) { |
| | | LOG(ERROR) << e.what(); |
| | | return; |
| | | LOG(ERROR) << "Error when run vad onnx forword: " << (e.what()); |
| | | exit(0); |
| | | } |
| | | |
| | | // 5. Change infer result to output shapes |
| | |
| | | try{ |
| | | using namespace std; |
| | | ifstream cmvn_stream(filename); |
| | | if (!cmvn_stream.is_open()) { |
| | | LOG(ERROR) << "Failed to open file: " << filename; |
| | | exit(0); |
| | | } |
| | | string line; |
| | | |
| | | while (getline(cmvn_stream, line)) { |
| | |
| | | } |
| | | } |
| | | |
| | | std::vector<std::vector<float>> &FsmnVad::LfrCmvn(std::vector<std::vector<float>> &vad_feats, int lfr_m, int lfr_n) { |
| | | std::vector<std::vector<float>> &FsmnVad::LfrCmvn(std::vector<std::vector<float>> &vad_feats) { |
| | | |
| | | std::vector<std::vector<float>> out_feats; |
| | | int T = vad_feats.size(); |
| | |
| | | std::vector<std::vector<float>> vad_feats; |
| | | std::vector<std::vector<float>> vad_probs; |
| | | FbankKaldi(vad_sample_rate_, vad_feats, waves); |
| | | vad_feats = LfrCmvn(vad_feats, 5, 1); |
| | | vad_feats = LfrCmvn(vad_feats); |
| | | Forward(vad_feats, &vad_probs); |
| | | |
| | | E2EVadModel vad_scorer = E2EVadModel(); |
| | |
| | | vad_segments = vad_scorer(vad_probs, waves, true, false, vad_silence_duration_, vad_max_len_, |
| | | vad_speech_noise_thres_, vad_sample_rate_); |
| | | return vad_segments; |
| | | |
| | | } |
| | | |
| | | void FsmnVad::InitCache(){ |