features.h
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// sherpa/csrc/features.h
//
// Copyright (c) 2023 Xiaomi Corporation
#ifndef SHERPA_ONNX_CSRC_FEATURES_H_
#define SHERPA_ONNX_CSRC_FEATURES_H_
#include <memory>
#include <mutex> // NOLINT
#include <vector>
#include "kaldi-native-fbank/csrc/online-feature.h"
namespace sherpa_onnx {
class FeatureExtractor {
public:
FeatureExtractor();
explicit FeatureExtractor(const knf::FbankOptions &fbank_opts);
/**
@param sampling_rate The sampling_rate of the input waveform. Should match
the one expected by the feature extractor.
@param waveform Pointer to a 1-D array of size n
@param n Number of entries in waveform
*/
void AcceptWaveform(float sampling_rate, const float *waveform, int32_t n);
// InputFinished() tells the class you won't be providing any
// more waveform. This will help flush out the last frame or two
// of features, in the case where snip-edges == false; it also
// affects the return value of IsLastFrame().
void InputFinished();
int32_t NumFramesReady() const;
// Note: IsLastFrame() will only ever return true if you have called
// InputFinished() (and this frame is the last frame).
bool IsLastFrame(int32_t frame) const;
/** Get n frames starting from the given frame index.
*
* @param frame_index The starting frame index
* @param n Number of frames to get.
* @return Return a 2-D tensor of shape (n, feature_dim).
* which is flattened into a 1-D vector (flattened in in row major)
*/
std::vector<float> GetFrames(int32_t frame_index, int32_t n) const;
void Reset();
int32_t FeatureDim() const { return opts_.mel_opts.num_bins; }
private:
std::unique_ptr<knf::OnlineFbank> fbank_;
knf::FbankOptions opts_;
mutable std::mutex mutex_;
};
} // namespace sherpa_onnx
#endif // SHERPA_ONNX_CSRC_FEATURES_H_