Google Inc.

Other

Christopher Thaddeus Hughes

Matthew Nirvan Sharifi

Diego Melendo Casado

Alexander Houston Gruenstein

Kenneth Edward Mixter

Terry Tai

Turaj Zakizadeh Shabestary

Yiteng Huang

Taylor Applebaum

Ignacio Lopez Moreno

Aleksandar Kracun

Richard Francis Lyon

Ryan Michael Rifkin

Pascal Tom Getreuer

Yuxuan Wang

Techniques are described for selectively adapting and/or selectively utilizing a noise reduction technique in detection of one or more features of a stream of audio data frames. For example, various techniques are directed to selectively adapting and/or utilizing a noise reduction technique in detection of an invocation phrase in a stream of audio data frames, detection of voice characteristics in a stream of audio data frames (e.g., for speaker identification), etc. Utilization of described techniques can result in more robust and/or more accurate detections of features of a stream of audio data frames in various situations, such as in environments with strong background noise. In various implementations, described techniques are implemented in combination with an automated assistant, and feature(s) detected utilizing techniques described herein are utilized to adapt the functionality of the automated assistant.

Selective adaptation and utilization of noise reduction technique in invocation phrase detection

The various implementations described herein include methods and systems for determining device leadership among voice interface devices. In one aspect, a method is performed at a first electronic device of a plurality of electronic devices, each having microphones, a speaker, processors, and memory storing programs for execution by the processors. The first device detects a voice input. It determines a device state and a relevance of the voice input. It identifies a subset of electronic devices from the plurality to which the voice input is relevant. In accordance with a determination that the subset includes the first device, the first device determines a first score of a criterion associated with the voice input and receives second scores of the criterion from other devices in the subset. In accordance with a determination that the first score is higher than the second scores, the first device responds to the detected input.

Device leadership negotiation among voice interface devices

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for contextual hotwords are disclosed. In one aspect, a method, during a boot process of a computing device, includes the actions of determining, by a computing device, a context associated with the computing device. The actions further include, based on the context associated with the computing device, determining a hotword. The actions further include, after determining the hotword, receiving audio data that corresponds to an utterance. The actions further include determining that the audio data includes the hotword. The actions further include, in response to determining that the audio data includes the hotword, performing an operation associated with the hotword.

Contextual hotwords

A permanent below-ground flood barrier installation is characterized by a trench surrounding a specified area. A concrete ballast lines the trench and anchors a covered housing containing a flexible water impermeable fabric wall and a series of supports. When a flood is impending the housing is opened, the supports removed and set up vertically at ground level, and the fabric wall extended upward. The fabric wall is attached at its upper edge to the cover set atop the supports, and at its lower edge to the housing. Three point anchoring of the supports maintain them in vertical orientation and stop means prevent backward movement during storm surges. When flooding subsides the components can be cleaned, dried and returned to the housing. No tools or special skills are required to set up the wall and supports once the initial installation has been completed.

Permanent below ground flood barrier installation

Techniques are described for selectively adapting and/or selectively utilizing a noise reduction technique in detection of one or more features of a stream of audio data frames. Various techniques are directed to selectively adapting and/or utilizing a noise reduction technique in detection of an invocation phrase in a stream of audio data frames, detection of voice characteristics in a stream of audio data frames (e.g., for speaker identification), etc. Utilization of described techniques can result in more robust and/or more accurate detections of features of a stream of audio data frames in various situations, such as in environments with strong background noise. In various implementations, described techniques are implemented in combination with an automated assistant, and feature(s) detected utilizing techniques described herein are utilized to adapt the functionality of the automated assistant.

The various implementations described herein include methods, devices, and systems for recognizing speech, such as user commands. In one aspect, a method includes: (1) receiving audio input data via the one or more microphones; (2) generating a plurality of energy channels for the audio input data; (3) generating a feature vector by performing a per-channel normalization to each channel of the plurality of energy channels; and (4) obtaining recognized speech from the audio input utilizing the feature vector.

Systems and methods for recognizing user speech

The various implementations described herein include methods and systems for determining device leadership among voice interface devices. In one aspect, a method is performed at an electronic device that includes microphones, a speaker, processors, and memory storing one or more programs for execution by the one or more processors. The electronic device: (1) detects a voice input; (2) determines a first quality score for the detected voice input; (3) receives quality scores generated by other electronic devices for detection of the voice input by the other electronic devices; (4) in accordance with a determination that the first quality score is not the highest amongst the quality scores for the voice input, identifies a criterion associated with the voice input; and (5) in accordance with a determination that the identified criterion is the most relevant to the electronic device, responds to the detected input.

A method at a first electronic device of multiple electronic devices, each electronic device of the plurality of electronic devices including one or more microphones and a speaker, includes detecting a voice input; determining a quality score for the detected voice input; communicating the quality score to the other devices of the plurality of electronic devices; receiving quality scores generated by the other devices for detection of the voice input by the other devices; if the quality score generated by the first electronic device is the highest amongst the quality scores, outputting an audible and/or visual response to the detected voice input, where the other devices of the plurality of electronic devices forgo outputting an audible response to the detected voice input; and if the quality score generated by the first electronic device is not the highest amongst the quality scores, forgoing outputting a response to the detected voice input.

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Redwood City, CA, United States of America

Christopher Thaddeus Hughes