Amazon Technologies, Inc.

Canyon IP Holdings, LLC

Rawles LLC

Jeffrey Penrod Adams

Kenneth John Basye

Stan Weidner Salvador

Gregory Michael Hart

Ryan Paul Thomas

Rajiv Ramachandran

Charles S Rogers, Iii

Robert David Owen

Gilles Jean Roger Belin

Reinhard Kneser

Jeffrey Paul Lilly

Tony David

Hugh Evan Secker-Walker

Frederick Victor Weber

Mahesh Krishnamoorthy

Alok Ulhas Parlikar

Christopher D Coley

Vikram Kumar Gundeti

Ariya Rastrow

Bjorn Hoffmeister

Fred Torok

Lambert Leo Mathias

Imre Attila Kiss

Jeffrey C O'Neill

Michal Tadeusz Kaszczuk

Adam Franciszek Nadolski

Frédéric Johan Georges Deramat

Kenneth Paul Fishkin

Ramy Sammy Sadek

Joshua Pollack

Colleen Maree Aubrey

Andrew Jake Rosenbaum

An interactive system may be implemented in part by an audio device located within a user environment, which may accept speech commands from a user and may also interact with the user by means of generated speech. In order to improve performance of the interactive system, a user may use a separate device, such as a personal computer or mobile device, to access a graphical user interface that lists details of historical speech interactions. The graphical user interface may be configured to allow the user to provide feedback and/or corrections regarding the details of specific interactions.

User feedback for speech interactions

A speech recognition system utilizing automatic speech recognition techniques such as end-pointing techniques in conjunction with beamforming and/or signal processing to isolate speech from one or more speaking users from multiple received audio signals and to detect the beginning and/or end of the speech based at least in part on the isolation. Audio capture devices such as microphones may be arranged in a beamforming array to receive the multiple audio signals. Multiple audio sources including speech may be identified in different beams and processed.

Direction based end-pointing for speech recognition

Power consumption for a computing device may be managed by one or more keywords. For example, if an audio input obtained by the computing device includes a keyword, a network interface module and/or an application processing module of the computing device may be activated. The audio input may then be transmitted via the network interface module to a remote computing device, such as a speech recognition server. Alternately, the computing device may be provided with a speech recognition engine configured to process the audio input for on-device speech recognition.

Speech recognition power management

In a voice controlled system, multiple applications are configured to respond to various commands. The voice controlled system includes client devices and servers. The correct application to receive a natural language command is identified based on how well the command matches functions of the application. A target application to receive the command may additionally be selected based on which application is most likely to receive a command. Likelihood of an application receiving a command may be determined by considering context. The command may be a voice input to a client device that is analyzed by speech recognition technology to determine word strings representing possible commands. Thus, the selection of a target application to receive the command may be based on word strings from the natural language input, a closeness of fit between the command and an application, and/or the likelihood an application is the target for the next incoming command.

Routing natural language commands to the appropriate applications

An automatic speech recognition (ASR) device may be configured to predict pronunciations of textual identifiers (for example, song names, etc.) based on predicting one or more languages of origin of the textual identifier. The one or more languages of origin may be determined based on the textual identifier. The pronunciations may include a hybrid pronunciation including a pronunciation in one language, a pronunciation in a second language and a hybrid pronunciation that combines multiple languages. The pronunciations may be added to a lexicon and matched to the content item (e.g., song) and/or textual identifier. The ASR device may receive a spoken utterance from a user requesting the ASR device to access the content item. The ASR device determines whether the spoken utterance matches one of the pronunciations of the content item in the lexicon. The ASR device then accesses the content when the spoken utterance matches one of the potential textual identifier pronunciations.

Predicting pronunciation in speech recognition

A home interface comprises one or more audio interfaces within the premises of users. The audio interfaces are connected to an assistant service that detects conditions within rooms of user premises and that generates simulated audio themes for the rooms. The audio themes may be changed depending on detected conditions, and subthemes of a given audio theme may be implemented in different rooms.

Audio themes

Features are disclosed for presenting multiple media items based on one or more rules defining how the items are to be presented. One media item may be presented, and during presentation any number of additional media items may be received or scheduled for presentation. Rules may define which media items have priority over others, which media items may interrupt others or be interrupted, which media items may be delayed or presented early, whether particular media items are time-critical such that they are not to be delayed but rather should take presentation priority over others, etc. Metadata may be associated with particular media items or categories thereof. The metadata can provide details regarding how the rules should be applied to those media items. User feedback may also be obtained, and may affect the further application of the rules.

Rule-based presentation of media items

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Tyngsborough, MA, United States of America

Jeffrey Penrod Adams