Audio data augmentation for machine learning object classification

Abstract

This application discloses a computing system to receive audio data corresponding to sounds emitted by objects capable of being identified in an environment. The audio data includes labels identifying types of the objects emitting the sounds. The computing system alters the audio data to generate an augmented audio data set by modifying a timing of the audio data, adjusting an amplitude of the audio data, incorporating noise corresponding to different traffic environments into the audio data, or dampening noise in the audio data. The computing system can label the augmented audio data set with the labels of the audio data altered to generate the augmented audio data set. A machine-learning classification system can be trained with the augmented audio data set, which configures machine-learning classification system to classify objects from audio measurements captured with one or more audio devices configured to sense the environment.

Dependencies are inferred from the claim text.