


Initialize the stft and istft modules
stft = Spectrogram(n_fft=1024, hop_length=256, return_complex=True, power=None)
istft = InverseSpectrogram(n_fft=1024, hop_length=256)
Get the noisy spectrogram
specgram_mix = stft(waveform_mix)
Get the Time-Frequency mask via machine learning models
mask = model(waveform)
Initialize the MVDR module
mvdr = MVDR(ref_channel=0, solution=”ref_channel”, multi_mask=False)
Apply MVDR beamforming
specgram_enhanced = mvdr(specgram_mix, mask)
Get the enhanced waveform via iSTFT
waveform_enhanced = istft(specgram_enhanced, length=waveform.shape[-1])
```
Please refer to the documentation for more details and try out this feature using the MVDR tutorial.



(Beta) RNN Transducer Loss