// sherpa-onnx/csrc/offline-stream.h // // Copyright (c) 2023 Xiaomi Corporation #ifndef SHERPA_ONNX_CSRC_OFFLINE_STREAM_H_ #define SHERPA_ONNX_CSRC_OFFLINE_STREAM_H_ #include #include #include #include #include "sherpa-onnx/csrc/parse-options.h" namespace sherpa_onnx { struct OfflineRecognitionResult; struct OfflineFeatureExtractorConfig { // Sampling rate used by the feature extractor. If it is different from // the sampling rate of the input waveform, we will do resampling inside. int32_t sampling_rate = 16000; // Feature dimension int32_t feature_dim = 80; std::string ToString() const; void Register(ParseOptions *po); }; class OfflineStream { public: explicit OfflineStream(const OfflineFeatureExtractorConfig &config = {}); ~OfflineStream(); /** @param sampling_rate The sampling_rate of the input waveform. If it does not equal to config.sampling_rate, we will do resampling inside. @param waveform Pointer to a 1-D array of size n. It must be normalized to the range [-1, 1]. @param n Number of entries in waveform Caution: You can only invoke this function once so you have to input all the samples at once */ void AcceptWaveform(int32_t sampling_rate, const float *waveform, int32_t n) const; /// Return feature dim of this extractor int32_t FeatureDim() const; // Get all the feature frames of this stream in a 1-D array, which is // flattened from a 2-D array of shape (num_frames, feat_dim). std::vector GetFrames() const; /** Set the recognition result for this stream. */ void SetResult(const OfflineRecognitionResult &r); /** Get the recognition result of this stream */ const OfflineRecognitionResult &GetResult() const; private: class Impl; std::unique_ptr impl_; }; } // namespace sherpa_onnx #endif // SHERPA_ONNX_CSRC_OFFLINE_STREAM_H_