Google Inc.

Karolis Misiunas

Jamie Alexander Zyskowski

Mohamad Hassan Bin Mohamad Rom

Dominik Roblek

Marco Tagliasacchi

Beat Gfeller

Kelly Elizabeth Dobson

Zalán Borsos

Félix De Chaumont Quitry

Thomas William Inskip, Vi

Hannah Muckenhirn

Yunpeng Li

Vahe Tshitoyan

Thomás William Inskip, Vi

Oleg Rybakov

Victor Ungureanu

Brian Foo

Julian Maclaren

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for processing an input audio waveform using a generator neural network to generate an output audio waveform. In one aspect, a method comprises: receiving an input audio waveform; processing the input audio waveform using an encoder neural network to generate a set of feature vectors representing the input audio waveform; and processing the set of feature vectors representing the input audio waveform using a decoder neural network to generate an output audio waveform that comprises a respective output audio sample for each of a plurality of output time steps.

Generating audio waveforms using encoder and decoder neural networks

Various systems, devices, and methods for social interaction measurement that preserve privacy are presented. An audio signal can be captured using a microphone. The audio signal can be processed using an audio-based machine learning model that is trained to detect the presence of speech. The audio signal can be discarded such that content of the audio signal is not stored after the audio signal is processed using the machine learning model. An indication of whether speech is present within the audio signal can be output based at least in part on processing the audio signal using the audio-based machine learning model.

Privacy-preserving social interaction measurement

Methods, systems, devices, and computer-readable storage media for activity detection of a user of a computing device, using multi-modal sensing. A device can be configured to receive sensor data corresponding to multiple modalities and process the sensor data to predict an activity performed by a user of a computing device. The device in response to the detected activity can perform a response action, such as muting or pausing audio playback from the computing device. Different modalities can be combined, such as body vibration data, air vibration data, and image data, which can be processed to distinguish user activity, e.g., speaking versus not speaking, to allow the computing device to perform the correct corresponding action.

Activity detection on devices with multi-modal sensing

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Zurich, Switzerland

Karolis Misiunas