71 lines
1.9 KiB
C++
71 lines
1.9 KiB
C++
// sherpa-onnx/csrc/features.h
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//
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// Copyright (c) 2023 Xiaomi Corporation
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#ifndef SHERPA_ONNX_CSRC_FEATURES_H_
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#define SHERPA_ONNX_CSRC_FEATURES_H_
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#include <memory>
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#include <string>
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#include <vector>
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namespace sherpa_onnx {
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struct FeatureExtractorConfig {
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float sampling_rate = 16000;
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int32_t feature_dim = 80;
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std::string ToString() const;
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};
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class FeatureExtractor {
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public:
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explicit FeatureExtractor(const FeatureExtractorConfig &config = {});
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~FeatureExtractor();
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/**
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@param sampling_rate The sampling_rate of the input waveform. Should match
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the one expected by the feature extractor.
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@param waveform Pointer to a 1-D array of size n
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@param n Number of entries in waveform
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*/
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void AcceptWaveform(float sampling_rate, const float *waveform, int32_t n);
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/**
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* InputFinished() tells the class you won't be providing any
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* more waveform. This will help flush out the last frame or two
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* of features, in the case where snip-edges == false; it also
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* affects the return value of IsLastFrame().
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*/
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void InputFinished();
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int32_t NumFramesReady() const;
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/** Note: IsLastFrame() will only ever return true if you have called
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* InputFinished() (and this frame is the last frame).
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*/
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bool IsLastFrame(int32_t frame) const;
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/** Get n frames starting from the given frame index.
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*
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* @param frame_index The starting frame index
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* @param n Number of frames to get.
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* @return Return a 2-D tensor of shape (n, feature_dim).
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* which is flattened into a 1-D vector (flattened in in row major)
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*/
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std::vector<float> GetFrames(int32_t frame_index, int32_t n) const;
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void Reset();
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/// Return feature dim of this extractor
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int32_t FeatureDim() const;
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private:
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class Impl;
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std::unique_ptr<Impl> impl_;
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};
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} // namespace sherpa_onnx
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#endif // SHERPA_ONNX_CSRC_FEATURES_H_
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