audio_zen/acoustics/beamforming.py
def apply_beamformer_vector_at_utterance_level(
        beamforming_vector: ComplexTensor,
        mixture: ComplexTensor
) -> ComplexTensor:
    """Apply beamforming weights at utterance level

    Args:
        beamforming_vector: beamforming weighted vector with shape of [..., C]
        mixture: mixture of shape [..., C, T]

    Notes:
        For each frequency and omit time variation.

    Returns:
        [B, F, T]
    """
    return FC.einsum("...c, ...ct -> ...t", [beamforming_vector.conj(), mixture])
Apply beamforming weights at utterance level

    Args:
        beamforming_vector: beamforming weighted vector with shape of [..., C]
        mixture: mixture of shape [..., C, T]

    Notes:
        For each frequency and omit time variation.

    Returns:
        [B, F, T]
    
Apply beamforming weights at utterance level
Apply beamforming weights at utterance level
def apply_beamformer_vector_at_utterance_level(
        beamforming_vector: ComplexTensor,
        mixture: ComplexTensor
) -> ComplexTensor:
    return FC.einsum("...c, ...ct -> ...t", [beamforming_vector.conj(), mixture])
def apply_beamformer_vector_at_utterance_level ( beamforming_vector : ComplexTensor , mixture : ComplexTensor ) -> ComplexTensor : return FC . einsum ( "...c, ...ct -> ...t" , [ beamforming_vector . conj ( ) , mixture ] )
Apply beamforming weights at utterance level
Apply beamforming weights at utterance level
"""Apply beamforming weights at utterance level

    Args:
        beamforming_vector: beamforming weighted vector with shape of [..., C]
        mixture: mixture of shape [..., C, T]

    Notes:
        For each frequency and omit time variation.

    Returns:
        [B, F, T]
    """
None
beamforming_vector
ComplexTensor
beamforming weighted vector with shape of [..., C]
beamforming weighted vector with shape of [ ... C ]
mixture
ComplexTensor
mixture of shape [..., C, T]
mixture of shape [ ... C T ]