def test_read_wav_internal(self): fs, wav = wavfile.read(self.mono_wav, False) wave_data = feat.read_wav_kaldi_internal(wav, fs) # Correct number of channels self.assertEqual(wave_data.data().num_rows, 1) # Correct number of samples self.assertEqual(wav.shape[0], wave_data.data().num_cols)
def get_ppg(wav_path, deps): """ Input: wav_path: *.wav path deps = DependenciesPPG() Library: from scipy.io import wavfile from common import feat """ fs, wav = wavfile.read(wav_path) wave_data = feat.read_wav_kaldi_internal(wav, fs) seq = ppg.compute_full_ppg_wrapper(wave_data, deps.nnet, deps.lda, 10) return seq
def get_monophone_ppg(self) -> ndarray: """A wrapper function to initialize the monophone ppg of this utterance. Requires non-empty waveform, fs, and kaldi_shift. Returns: The monophone ppgs in numpy ndarray format. """ if self.kaldi_shift < 1: # ms raise ValueError('Invalid frame kaldi frame shift parameter %d.', self.kaldi_shift) if self.wav.size == 0 or self.fs < 0: raise ValueError('To perform alignment, the object must contain ' 'valid speech data and sampling frequency.') wav_kaldi = read_wav_kaldi_internal(self.wav, self.fs) ppg_deps = ppg.DependenciesPPG() self.monophone_ppg = ppg.compute_monophone_ppg(wav_kaldi, ppg_deps.nnet, ppg_deps.lda, ppg_deps.monophone_trans, self.kaldi_shift) return self.monophone_ppg
def get_ppg(wav_path, deps): fs, wav = wavfile.read(wav_path) wave_data = feat.read_wav_kaldi_internal(wav, fs) seq = ppg.compute_full_ppg_wrapper(wave_data, deps.nnet, deps.lda, 10) return seq
def get_ppg(wav, fs): wave_data = feat.read_wav_kaldi_internal(wav, fs) seq = compute_full_ppg_wrapper(wave_data, ppg_deps.nnet, ppg_deps.lda, mel_window_step) return seq