Google Inc.

Andrew Hines

Jan K Skoglund

Anil Christopher Kokaram

Andrew Allen

Miroslaw Narbutt

Naomi Harte

Noami A Harte

A computing device includes a processor and a memory. The processor is configured to generate spectrograms, for example, using short-time Fourier transform, for a plurality of channels of reference and test ambisonic signals. In some implementations, the test ambisonic signal may be generated by decoding an encoded version of the reference ambisonic signal. The processor is further configured to compare, for each of the plurality of channels of a reference ambisonic signal, at least a patch associated with a channel of the reference ambisonic signal with at least a corresponding patch of a corresponding channel of the test ambisonic signal and determine a localization accuracy of the test ambisonic signal based on the comparison. In some implementations, the comparing may be based on phaseograms of the reference and test ambisonic signals.

Objective quality metrics for ambisonic spatial audio

Methods and systems are provided for using a model of human speech quality perception to provide an objective measure for predicting subjective quality assessments. A Virtual Speech Quality Objective Listener (ViSQOL) model is a signal-based full-reference metric that uses a spectro-temporal measure of similarity between a reference signal and test speech signal. Specifically, the model provides for the ability to detect and predict the level of clock drift, and determine whether such clock drift will impact a listener's quality of experience.

Objective speech quality metric

Methods and systems are provided for detecting chop in an audio signal. A time-frequency representation, such as a spectrogram, is created for an audio signal and used to calculate a gradient of mean power per frame of the audio signal. Positive and negative gradients are defined for the signal based on the gradient of mean power, and a maximum overlap offset between the positive and negative gradients is determined by calculating a value that maximizes the cross-correlation of the positive and negative gradients. The negative gradient values may be combined (e.g., summed) with the overlap offset, and the combined values then compared with a threshold to estimate the amount of chop present in the audio signal. The chop detection model provided is low-complexity and is applicable to narrowband, wideband, and superwideband speech.

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Andrew Hines