/**
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* Copyright FunASR (https://github.com/alibaba-damo-academy/FunASR). All Rights Reserved.
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* MIT License (https://opensource.org/licenses/MIT)
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*/
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#ifndef VAD_SERVER_FSMNVAD_H
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#define VAD_SERVER_FSMNVAD_H
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#include "precomp.h"
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namespace funasr {
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class FsmnVad : public VadModel {
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/**
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* Author: Speech Lab of DAMO Academy, Alibaba Group
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* Deep-FSMN for Large Vocabulary Continuous Speech Recognition
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* https://arxiv.org/abs/1803.05030
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*/
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public:
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FsmnVad();
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~FsmnVad();
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void Test();
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void InitVad(const std::string &vad_model, const std::string &vad_cmvn, const std::string &vad_config, int thread_num);
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std::vector<std::vector<int>> Infer(std::vector<float> &waves, bool input_finished=true);
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void Forward(
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const std::vector<std::vector<float>> &chunk_feats,
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std::vector<std::vector<float>> *out_prob,
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std::vector<std::vector<float>> *in_cache,
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bool is_final);
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void Reset();
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std::shared_ptr<Ort::Session> vad_session_ = nullptr;
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Ort::Env env_;
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Ort::SessionOptions session_options_;
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std::vector<const char *> vad_in_names_;
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std::vector<const char *> vad_out_names_;
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std::vector<std::vector<float>> in_cache_;
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knf::FbankOptions fbank_opts_;
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std::vector<float> means_list_;
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std::vector<float> vars_list_;
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int vad_sample_rate_ = MODEL_SAMPLE_RATE;
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int vad_silence_duration_ = VAD_SILENCE_DURATION;
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int vad_max_len_ = VAD_MAX_LEN;
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double vad_speech_noise_thres_ = VAD_SPEECH_NOISE_THRES;
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int lfr_m = VAD_LFR_M;
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int lfr_n = VAD_LFR_N;
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private:
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void ReadModel(const char* vad_model);
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void LoadConfigFromYaml(const char* filename);
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static void GetInputOutputInfo(
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const std::shared_ptr<Ort::Session> &session,
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std::vector<const char *> *in_names, std::vector<const char *> *out_names);
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void FbankKaldi(float sample_rate, std::vector<std::vector<float>> &vad_feats,
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std::vector<float> &waves);
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void LfrCmvn(std::vector<std::vector<float>> &vad_feats);
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void LoadCmvn(const char *filename);
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void InitCache();
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};
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} // namespace funasr
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#endif //VAD_SERVER_FSMNVAD_H
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