espnet2.enh.layers.beamformer.get_rtf

source

espnet2.enh.layers.beamformer.get_rtf(psd_speech, psd_noise, mode='power', reference_vector: int | Tensor = 0, iterations: int = 3)

Calculate the relative transfer function (RTF)

Algorithm of power method: : 1. rtf = reference_vector 2. for i in range(iterations): : rtf = (psd_noise^-1 @ psd_speech) @ rtf rtf = rtf / ||rtf||_2 # this normalization can be skipped 3. rtf = psd_noise @ rtf 4. rtf = rtf / rtf[…, ref_channel, :]

Note: 4) Normalization at the reference channel is not performed here.

• Parameters:
  • psd_speech (torch.complex64/ComplexTensor) – speech covariance matrix (…, F, C, C)
  • psd_noise (torch.complex64/ComplexTensor) – noise covariance matrix (…, F, C, C)
  • mode (str) – one of (“power”, “evd”) “power”: power method “evd”: eigenvalue decomposition
  • reference_vector (torch.Tensor or int) – (…, C) or scalar
  • iterations (int) – number of iterations in power method
• Returns: (…, F, C, 1)
• Return type: rtf (torch.complex64/ComplexTensor)