Distance based Sound Separation using Machine Learning Models

A computer-implemented method of applying a trained neural network for distance based sound separation, comprising:

• receiving, by an audio input component of a computing device, an audio mixture from one or more sources;
• predicting, by the trained neural network, one or more near sounds and one or more far sounds from the audio mixture, wherein the one or more near sounds correspond to first sources that are proximate to the audio input component, and the one or more far sounds correspond to second sources that are not proximate to the audio input component, wherein the predicting is based on acoustic characteristics of the received audio mixture, the neural network having been trained on training data comprising a plurality of audio mixtures, wherein a given audio mixture of the plurality of audio mixtures comprises respective one or more first sounds that are proximate to a respective audio input component receiving the given audio mixture, and respective one or more second sounds that are not proximate to the respective audio input component, the synthetic training data having been generated by an acoustic simulator to capture acoustic characteristics that vary based on a respective distance from the respective audio input component;
• and
• providing, by the computing device, the predicted one or more near sounds.

A computing device for distance based sound separation, comprising:

• one or more processors;
• and
• data storage, wherein the data storage has stored thereon computer-executable instructions that, when executed by the one or more processors, cause the computing device to carry out functions comprising:
• receiving, by the computing device, synthetic training data comprising a plurality of audio mixtures, wherein each audio mixture comprises respective one or more first sounds that are proximate to a respective audio input component receiving the audio mixture, and respective one or more second sounds that are not proximate to the respective audio input component, the synthetic training data having been generated by an acoustic simulator to capture acoustic characteristics that vary based on a respective distance from the respective audio input component;
• training, based on the training data, a neural network to predict one or more near sounds and one or more far sounds in a particular audio mixture received by a particular audio input component, wherein the one or more near sounds correspond to first sources that are proximate to the particular audio input component, and the one or more far sounds correspond to second sources that are not proximate to the particular audio input component, wherein the predicting is based on particular acoustic characteristics of the particular audio mixture;
• and
• providing, by the computing device, the trained neural network.

A computing device for applying a trained neural network for distance based sound separation, comprising:

• one or more processors;
• and
• data storage, wherein the data storage has stored thereon computer-executable instructions that, when executed by the one or more processors, cause the computing device to carry out functions comprising:
• receiving, by an audio input component of a computing device, an audio mixture from one or more sources;
• predicting, by the trained neural network, one or more near sounds and one or more far sounds from the audio mixture, wherein the one or more near sounds correspond to first sources that are proximate to the audio input component, and the one or more far sounds correspond to second sources that are not proximate to the audio input component, wherein the predicting is based on acoustic characteristics of the received audio mixture, the neural network having been trained on training data comprising a plurality of audio mixtures, wherein a given audio mixture of the plurality of audio mixtures comprises respective one or more first sounds that are proximate to a respective audio input component receiving the given audio mixture, and respective one or more second sounds that are not proximate to the respective audio input component, the synthetic training data having been generated by an acoustic simulator to capture acoustic characteristics that vary based on a respective distance from the respective audio input component;
• and
• providing, by the computing device, the predicted one or more near sounds.