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| #ifndef SILERO_TORCH_H |
| #define SILERO_TORCH_H |
|
|
| #include <string> |
| #include <memory> |
| #include <stdexcept> |
| #include <iostream> |
| #include <memory> |
| #include <vector> |
| #include <fstream> |
| #include <chrono> |
|
|
| #include <torch/torch.h> |
| #include <torch/script.h> |
|
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|
| namespace silero{ |
|
|
| struct SpeechSegment{ |
| int start; |
| int end; |
| }; |
|
|
| class VadIterator{ |
| public: |
|
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| VadIterator(const std::string &model_path, float threshold = 0.5, int sample_rate = 16000, |
| int window_size_ms = 32, int speech_pad_ms = 30, int min_silence_duration_ms = 100, |
| int min_speech_duration_ms = 250, int max_duration_merge_ms = 300, bool print_as_samples = false); |
| ~VadIterator(); |
|
|
|
|
| void SpeechProbs(std::vector<float>& input_wav); |
| std::vector<silero::SpeechSegment> GetSpeechTimestamps(); |
| void SetVariables(); |
|
|
| float threshold; |
| int sample_rate; |
| int window_size_ms; |
| int min_speech_duration_ms; |
| int max_duration_merge_ms; |
| bool print_as_samples; |
|
|
| private: |
| torch::jit::script::Module model; |
| std::vector<float> outputs_prob; |
| int min_silence_samples; |
| int min_speech_samples; |
| int speech_pad_samples; |
| int window_size_samples; |
| int duration_merge_samples; |
| int current_sample = 0; |
|
|
| int total_sample_size=0; |
|
|
| int min_silence_duration_ms; |
| int speech_pad_ms; |
| bool triggered = false; |
| int temp_end = 0; |
|
|
| void init_engine(int window_size_ms); |
| void init_torch_model(const std::string& model_path); |
| void reset_states(); |
| std::vector<SpeechSegment> DoVad(); |
| std::vector<SpeechSegment> mergeSpeeches(const std::vector<SpeechSegment>& speeches, int duration_merge_samples); |
|
|
| }; |
|
|
| } |
| #endif |
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