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https://github.com/modelscope/FunASR
synced 2025-09-15 14:48:36 +08:00
fix LfrCmvn for paraformer (#1097)
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862c521465
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@ -318,30 +318,20 @@ void Paraformer::Reset()
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{
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}
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vector<float> Paraformer::FbankKaldi(float sample_rate, const float* waves, int len) {
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void Paraformer::FbankKaldi(float sample_rate, const float* waves, int len, std::vector<std::vector<float>> &asr_feats) {
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knf::OnlineFbank fbank_(fbank_opts_);
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std::vector<float> buf(len);
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for (int32_t i = 0; i != len; ++i) {
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buf[i] = waves[i] * 32768;
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}
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fbank_.AcceptWaveform(sample_rate, buf.data(), buf.size());
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//fbank_->InputFinished();
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int32_t frames = fbank_.NumFramesReady();
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int32_t feature_dim = fbank_opts_.mel_opts.num_bins;
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vector<float> features(frames * feature_dim);
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float *p = features.data();
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//std::cout << "samples " << len << std::endl;
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//std::cout << "fbank frames " << frames << std::endl;
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//std::cout << "fbank dim " << feature_dim << std::endl;
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//std::cout << "feature size " << features.size() << std::endl;
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for (int32_t i = 0; i != frames; ++i) {
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const float *f = fbank_.GetFrame(i);
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std::copy(f, f + feature_dim, p);
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p += feature_dim;
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const float *frame = fbank_.GetFrame(i);
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std::vector<float> frame_vector(frame, frame + fbank_opts_.mel_opts.num_bins);
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asr_feats.emplace_back(frame_vector);
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}
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return features;
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}
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void Paraformer::LoadCmvn(const char *filename)
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@ -416,56 +406,65 @@ string Paraformer::FinalizeDecode(WfstDecoder* &wfst_decoder,
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return wfst_decoder->FinalizeDecode(is_stamp, us_alphas, us_cif_peak);
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}
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vector<float> Paraformer::ApplyLfr(const std::vector<float> &in)
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{
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int32_t in_feat_dim = fbank_opts_.mel_opts.num_bins;
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int32_t in_num_frames = in.size() / in_feat_dim;
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int32_t out_num_frames =
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(in_num_frames - lfr_m) / lfr_n + 1;
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int32_t out_feat_dim = in_feat_dim * lfr_m;
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void Paraformer::LfrCmvn(std::vector<std::vector<float>> &asr_feats) {
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std::vector<float> out(out_num_frames * out_feat_dim);
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std::vector<std::vector<float>> out_feats;
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int T = asr_feats.size();
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int T_lrf = ceil(1.0 * T / lfr_n);
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const float *p_in = in.data();
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float *p_out = out.data();
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for (int32_t i = 0; i != out_num_frames; ++i) {
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std::copy(p_in, p_in + out_feat_dim, p_out);
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p_out += out_feat_dim;
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p_in += lfr_n * in_feat_dim;
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// Pad frames at start(copy first frame)
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for (int i = 0; i < (lfr_m - 1) / 2; i++) {
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asr_feats.insert(asr_feats.begin(), asr_feats[0]);
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}
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return out;
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}
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void Paraformer::ApplyCmvn(std::vector<float> *v)
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{
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int32_t dim = means_list_.size();
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int32_t num_frames = v->size() / dim;
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float *p = v->data();
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for (int32_t i = 0; i != num_frames; ++i) {
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for (int32_t k = 0; k != dim; ++k) {
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p[k] = (p[k] + means_list_[k]) * vars_list_[k];
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}
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p += dim;
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// Merge lfr_m frames as one,lfr_n frames per window
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T = T + (lfr_m - 1) / 2;
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std::vector<float> p;
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for (int i = 0; i < T_lrf; i++) {
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if (lfr_m <= T - i * lfr_n) {
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for (int j = 0; j < lfr_m; j++) {
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p.insert(p.end(), asr_feats[i * lfr_n + j].begin(), asr_feats[i * lfr_n + j].end());
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}
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out_feats.emplace_back(p);
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p.clear();
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} else {
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// Fill to lfr_m frames at last window if less than lfr_m frames (copy last frame)
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int num_padding = lfr_m - (T - i * lfr_n);
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for (int j = 0; j < (asr_feats.size() - i * lfr_n); j++) {
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p.insert(p.end(), asr_feats[i * lfr_n + j].begin(), asr_feats[i * lfr_n + j].end());
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}
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for (int j = 0; j < num_padding; j++) {
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p.insert(p.end(), asr_feats[asr_feats.size() - 1].begin(), asr_feats[asr_feats.size() - 1].end());
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}
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out_feats.emplace_back(p);
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}
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}
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}
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// Apply cmvn
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for (auto &out_feat: out_feats) {
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for (int j = 0; j < means_list_.size(); j++) {
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out_feat[j] = (out_feat[j] + means_list_[j]) * vars_list_[j];
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}
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}
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asr_feats = out_feats;
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}
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string Paraformer::Forward(float* din, int len, bool input_finished, const std::vector<std::vector<float>> &hw_emb, void* decoder_handle)
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{
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WfstDecoder* wfst_decoder = (WfstDecoder*)decoder_handle;
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int32_t in_feat_dim = fbank_opts_.mel_opts.num_bins;
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std::vector<float> wav_feats = FbankKaldi(MODEL_SAMPLE_RATE, din, len);
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wav_feats = ApplyLfr(wav_feats);
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ApplyCmvn(&wav_feats);
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std::vector<std::vector<float>> asr_feats;
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FbankKaldi(MODEL_SAMPLE_RATE, din, len, asr_feats);
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if(asr_feats.size() == 0){
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return "";
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}
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LfrCmvn(asr_feats);
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int32_t feat_dim = lfr_m*in_feat_dim;
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int32_t num_frames = wav_feats.size() / feat_dim;
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//std::cout << "feat in: " << num_frames << " " << feat_dim << std::endl;
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int32_t num_frames = asr_feats.size();
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std::vector<float> wav_feats;
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for (const auto &frame_feat: asr_feats) {
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wav_feats.insert(wav_feats.end(), frame_feat.begin(), frame_feat.end());
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}
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#ifdef _WIN_X86
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Ort::MemoryInfo m_memoryInfo = Ort::MemoryInfo::CreateCpu(OrtDeviceAllocator, OrtMemTypeCPU);
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@ -28,8 +28,7 @@ namespace funasr {
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void LoadConfigFromYaml(const char* filename);
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void LoadOnlineConfigFromYaml(const char* filename);
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void LoadCmvn(const char *filename);
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vector<float> ApplyLfr(const vector<float> &in);
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void ApplyCmvn(vector<float> *v);
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void LfrCmvn(std::vector<std::vector<float>> &asr_feats);
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std::shared_ptr<Ort::Session> hw_m_session = nullptr;
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Ort::Env hw_env_;
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@ -51,7 +50,7 @@ namespace funasr {
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void InitSegDict(const std::string &seg_dict_model);
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std::vector<std::vector<float>> CompileHotwordEmbedding(std::string &hotwords);
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void Reset();
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vector<float> FbankKaldi(float sample_rate, const float* waves, int len);
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void FbankKaldi(float sample_rate, const float* waves, int len, std::vector<std::vector<float>> &asr_feats);
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string Forward(float* din, int len, bool input_finished=true, const std::vector<std::vector<float>> &hw_emb={{0.0}}, void* wfst_decoder=nullptr);
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string GreedySearch( float* in, int n_len, int64_t token_nums,
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bool is_stamp=false, std::vector<float> us_alphas={0}, std::vector<float> us_cif_peak={0});
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