| | |
|---|
| | | fs: int = 16000, |
|---|
| | | window: str = 'hamming', |
|---|
| | | n_mels: int = 80, |
|---|
| | | frame_length: int = 25.0, |
|---|
| | | frame_length: int = 25, |
|---|
| | | frame_shift: int = 10, |
|---|
| | | filter_length_min: int = -1, |
|---|
| | | filter_length_max: float = -1, |
|---|
| | |
|---|
| | | opts.mel_opts.debug_mel = False |
|---|
| | | self.opts = opts |
|---|
| | | |
|---|
| | | self.compute_fbank_feats = knf.OnlineFbank(self.opts) |
|---|
| | | |
|---|
| | | self.filter_length_min = filter_length_min |
|---|
| | | self.filter_length_max = filter_length_max |
|---|
| | | self.lfr_m = lfr_m |
|---|
| | |
|---|
| | | def fbank(self, |
|---|
| | | waveform: np.ndarray) -> Tuple[np.ndarray, np.ndarray]: |
|---|
| | | waveform = waveform * (1 << 15) |
|---|
| | | self.compute_fbank_feats.accept_waveform(self.opts.frame_opts.samp_freq, waveform.tolist()) |
|---|
| | | frames = self.compute_fbank_feats.num_frames_ready |
|---|
| | | fbank_fn = knf.OnlineFbank(self.opts) |
|---|
| | | fbank_fn.accept_waveform(self.opts.frame_opts.samp_freq, waveform.tolist()) |
|---|
| | | frames = fbank_fn.num_frames_ready |
|---|
| | | mat = np.empty([frames, self.opts.mel_opts.num_bins]) |
|---|
| | | for i in range(frames): |
|---|
| | | mat[i, :] = self.compute_fbank_feats.get_frame(i) |
|---|
| | | mat[i, :] = fbank_fn.get_frame(i) |
|---|
| | | feat = mat.astype(np.float32) |
|---|
| | | feat_len = np.array(mat.shape[0]).astype(np.int32) |
|---|
| | | return feat, feat_len |
|---|
