| | |
|---|
| | | |
|---|
| | | if self.cmvn_file: |
|---|
| | | self.cmvn = self.load_cmvn() |
|---|
| | | self.fbank_fn = None |
|---|
| | | self.fbank_beg_idx = 0 |
|---|
| | | |
|---|
| | | def fbank(self, |
|---|
| | | waveform: np.ndarray) -> Tuple[np.ndarray, np.ndarray]: |
|---|
| | | waveform = waveform * (1 << 15) |
|---|
| | | fbank_fn = knf.OnlineFbank(self.opts) |
|---|
| | | fbank_fn.accept_waveform(self.opts.frame_opts.samp_freq, waveform.tolist()) |
|---|
| | | frames = fbank_fn.num_frames_ready |
|---|
| | | self.fbank_fn = knf.OnlineFbank(self.opts) |
|---|
| | | self.fbank_fn.accept_waveform(self.opts.frame_opts.samp_freq, waveform.tolist()) |
|---|
| | | frames = self.fbank_fn.num_frames_ready |
|---|
| | | mat = np.empty([frames, self.opts.mel_opts.num_bins]) |
|---|
| | | for i in range(frames): |
|---|
| | | mat[i, :] = fbank_fn.get_frame(i) |
|---|
| | | mat[i, :] = self.fbank_fn.get_frame(i) |
|---|
| | | feat = mat.astype(np.float32) |
|---|
| | | feat_len = np.array(mat.shape[0]).astype(np.int32) |
|---|
| | | return feat, feat_len |
|---|
| | | |
|---|
| | | def fbank_online(self, |
|---|
| | | waveform: np.ndarray) -> Tuple[np.ndarray, np.ndarray]: |
|---|
| | | waveform = waveform * (1 << 15) |
|---|
| | | # self.fbank_fn = knf.OnlineFbank(self.opts) |
|---|
| | | self.fbank_fn.accept_waveform(self.opts.frame_opts.samp_freq, waveform.tolist()) |
|---|
| | | frames = self.fbank_fn.num_frames_ready |
|---|
| | | mat = np.empty([frames, self.opts.mel_opts.num_bins]) |
|---|
| | | for i in range(self.fbank_beg_idx, frames): |
|---|
| | | mat[i, :] = self.fbank_fn.get_frame(i) |
|---|
| | | self.fbank_beg_idx += (frames-self.fbank_beg_idx) |
|---|
| | | feat = mat.astype(np.float32) |
|---|
| | | feat_len = np.array(mat.shape[0]).astype(np.int32) |
|---|
| | | return feat, feat_len |
|---|
| | | |
|---|
| | | def reset_status(self): |
|---|
| | | self.fbank_fn = knf.OnlineFbank(self.opts) |
|---|
| | | self.fbank_beg_idx = 0 |
|---|
| | | |
|---|
| | | def lfr_cmvn(self, feat: np.ndarray) -> Tuple[np.ndarray, np.ndarray]: |
|---|
| | | if self.lfr_m != 1 or self.lfr_n != 1: |
|---|
| | | feat = self.apply_lfr(feat, self.lfr_m, self.lfr_n) |
|---|
