SOUND SOURCE ESTIMATION USING NEURAL NETWORKS

    公开(公告)号:US20170353789A1

    公开(公告)日:2017-12-07

    申请号:US15170348

    申请日:2016-06-01

    Applicant: Google Inc.

    Abstract: A system for estimating the location of a stationary or moving sound source includes multiple microphones, which need not be physically aligned in a linear array or a regular geometric pattern in a given environment, an auralizer that generates auralized multi-channel signals based at least on array-related transfer functions and room impulse responses of the microphones as well as signal labels corresponding to the auralized multi-channel signals, a feature extractor that extracts features from the auralized multi-channel signals for efficient processing, and a neural network that can be trained to estimate the location of the sound source based at least on the features extracted from the auralized multi-channel signals and the corresponding signal labels.

    Device specific multi-channel data compression

    公开(公告)号:US09875747B1

    公开(公告)日:2018-01-23

    申请号:US15211417

    申请日:2016-07-15

    Applicant: Google Inc.

    CPC classification number: G10L19/008 G10L19/0017 G10L25/30 G10L25/72

    Abstract: A sensor device may include a computing device in communication with multiple microphones. A neural network executing on the computing device may receive audio signals from each microphone. One microphone signal may serve as a reference signal. The neural network may extract differences in signal characteristics of the other microphone signals as compared to the reference signal. The neural network may combine these signal differences into a lossy compressed signal. The sensor device may transmit the lossy compressed signal and the lossless reference signal to a remote neural network executing in a cloud computing environment for decompression and sound recognition analysis.

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