4ef8f94ea8f6fc3cc1f35743e7c7af0b92ffb76b,nussl/separation/deep_separation.py,DeepSeparation,_compute_spectrograms,#DeepSeparation#,53

Before Change

        for i in range(self.audio_signal.num_channels):
            self.mel_spectrogram[i, :, :] = np.dot(magnitude[:, :, i].T, self.mel_filter_bank)

        self.mel_spectrogram = 10.0 * np.log10(self.mel_spectrogram**2 + 1e-7)
        self.silence_mask = self.mel_spectrogram > self.cutoff
        self.mel_spectrogram -= np.mean(self.mel_spectrogram)
        self.mel_spectrogram /= np.std(self.mel_spectrogram) + 1e-7
        return

After Change

        return model, metadata

    def _compute_spectrograms(self):
        self.audio_signal.stft_params.window_length = self.metadata["n_fft"]
        self.audio_signal.stft_params.hop_length = self.metadata["hop_length"]
        self.stft = self.audio_signal.stft(overwrite=True, remove_reflection=True,
                                           use_librosa=self.use_librosa_stft)
        

Instances