Microsoft Technology Licensing, LLC

James W Fosburgh

Dushyant Sharma

Patrick A Naylor

Do Yeong Kim

A method, computer program product, and computing system for estimating noise spectrum from a target audio signal segment. An acoustic neural embedding is generated from the target audio signal segment. An augmented audio signal segment is generated with background acoustic properties of the target audio signal segment by processing an input audio signal segment with the noise spectrum and the acoustic neural embedding using a neural network.

System and method for replicating background acoustic properties using neural networks

A method of performing at least de-reverberation and noise-reduction of an input sound signal of at least one input channel includes: performing, using at least one filter element, at least one of de-reverberation and noise-reduction of the input sound signal to generate a clean output sound signal; and determining, by a non-intrusive measure (NIM) estimation element, at least one non-intrusive measure (NIM) from the sound signal, wherein the at least one NIM includes at least one of voice activity detection (VAD) posterior, reverberation time, clarity index, direct-to-reverberant ratio (DRR), and signal-to-noise ratio (SNR); the de-reverberation is achieved by applying at least one channel shortening (CS) filter component of the at least one filter element in conjunction with the at least one NIM; and the noise reduction is performed in combination with the de-reverberation by the channel shortening (CS) filter component.

Method for neural beamforming, channel shortening and noise reduction

A method, computer program product, and computing system for receiving feature-based voice data associated with a first acoustic domain. One or more reverberation-based augmentations may be performed on at least a portion of the feature-based voice data, thus defining reverberation-augmented feature-based voice data.

System and method for data augmentation of feature-based voice data

A method, computer program product, and computing system for receiving feature-based voice data. One or more data augmentation characteristics may be received. One or more augmentations of the feature-based voice data may be generated, via a machine learning model, based upon, at least in part, the feature-based voice data and the one or more data augmentation characteristics.

A method, computer program product, and computing system for receiving feature-based voice data associated with a first acoustic domain. One or more gain-based augmentations may be performed on at least a portion of the feature-based voice data, thus defining gain-augmented feature-based voice data.

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Winchester, MA, United States of America

James W Fosburgh