A system for training a microphone geometry assisted encoder model and then utilizing the trained model to generate spatial audio signals that have been captured by a plurality of microphones. In a method for generating spatial audio signals, the method includes receiving geometry data related to a plurality of microphones of an audio capturing device and audio signal data captured by the plurality of microphones. The method also includes generating a spatial audio signal based on an output of a trained microphone geometry assisted encoder model. The trained microphone geometry assisted encoder model includes a geometry encoder configured to encode the geometry data and a signal encoder configured to encode the audio signal data. The trained microphone geometry assisted encoder model further includes a signal decoder having a plurality of layers and configured to generate the output upon which the spatial audio signal is based.

The present disclosure relates to an apparatus, that obtains a far-end signal and a near-end microphone signal, determines, based on at least the far-end signal, a far-end speech signal estimate and a far-end noise signal estimate, determines, based on at least the near-end microphone signal, a near-end microphone speech signal estimate and a near-end microphone noise signal estimate, determines, based on at least the far-end speech signal estimate and the near-end microphone speech signal estimate, a predicted near-end speech signal, determines, based on at least the far-end noise signal estimate and the near-end microphone noise signal estimate, a predicted near-end noise signal and outputs at least the predicted near-end speech signal and predicted near-end noise signal.