BACKGROUND

Speech processing systems are integrated into a variety of electronic devices. For example, many mobile phone devices have virtual assistants that utilize a natural language processing system configured to recognize speech and to perform one or more operations based on the recognized speech. Natural language processing is a relatively computationally expensive process. Accordingly, mobile phone devices (or other devices) that perform natural language processing may exhibit increased power consumption and therefore have reduced battery life as compared to other devices.

In order to reduce computational costs in natural language processing systems, some systems perform a relatively less computationally expensive voice activity detection process on a received sound signal and perform natural language processing on selected portions of the sound signal in which voice activity is detected (if any) rather than on the entire sound signal. Some such voice activity detection processes compare a sample of the sound signal to an estimate of background noise to determine whether voice activity is present in the sample. The estimate of background noise may be based on historical values associated with the sound signal. However, such systems may fail to detect voice activity that occurs following sudden loud noises represented in the sound signal.

SUMMARY

Systems and methods for detecting voice activity using non-linearly updated background noise estimation are disclosed.

A method includes selecting a frame of an audio signal. The method further includes determining a first power spectral density (PSD) distribution of the frame. The method further includes generating a first reference PSD distribution indicating an estimate of background noise in the frame based on a non-linear weight, a second reference PSD distribution of a previous frame of the audio signal, and a second PSD distribution of the previous frame. The method further includes determining whether voice activity is detected in the frame based on the first PSD distribution of the frame and the first reference PSD distribution.

A device includes a processor and a memory storing instructions executable by the processor to select a frame of an audio signal. The instructions are further executable by the processor to determine a first power spectral density (PSD) distribution of the frame. The instructions are further executable by the processor to generate a first reference PSD distribution indicating an estimate of background noise in the frame based on a non-linear weight, a second reference PSD distribution of a previous frame of the audio signal, and a second PSD distribution of the previous frame. The instructions are further executable by the processor to determine whether voice activity is detected in the frame based on the first PSD distribution of the frame and the first reference PSD distribution.

A computer readable storage device stores instructions executable by a processor to select a frame of an audio signal. The instructions are further executable by the processor to determine a first power spectral density (PSD) distribution of the frame. The instructions are further executable by the processor to generate a first reference PSD distribution indicating an estimate of background noise in the frame based on a non-linear weight, a second reference PSD distribution of a previous frame of the audio signal, and a second PSD distribution of the previous frame. The instructions are further executable by the processor to determine whether voice activity is detected in the frame based on the first PSD distribution of the frame and the first reference PSD distribution.

