Amazon Technologies, Inc.

Jyoti Chhabra

David Henry

Naveen Bobbili

Richard Du

Mark Vincent Mattione

Andrew Smith

Melanie C B Gens

Mark Lawrence

Sylvester-Jaron Dewey Ogletree

Raja Bose

Ramya Chaganti

Ryan McCrate

Zexiong Yan

Christopher Anthony James

Shekar Reddy

Eli Heitzman

Techniques for enabling access in a multi-assistant speech processing system are described, where a first assistant system may use components of a second assistant system as data processing components. Runtime operational data and user input data related to the first assistant may be kept separate from the processing data and input data related to the second assistant by propagating a first account ID, for user inputs directed to the first assistant, through the processing pipeline, and using a second account for user inputs directed to the second assistant. A mapping between the first account ID and the second account ID may be accessible to a select number of system components. Handoffs between the two assistants are handled in a manner where data related to one assistant is not accessible by the other assistant.

Data processing in a multi-assistant system

A speech-processing system may provide access to multiple virtual assistants via one or more voice-controlled devices. Each assistant may leverage language processing and language generation features of the speech-processing system, while handling different commands and/or providing access to different back applications. Each assistant may be associated with its own voice and/or speech style, and thus be perceived as having a particular 'personality.' Different assistants may be available for use with a particular voice-controlled device based on time, location, the particular user, etc. In some situations, language processing may be improved by leveraging data such as intent data, grammars, lexicons, entities, etc., associated with assistants available for use with the particular voice-controlled device.

Access to multiple virtual assistants

A system is provided for determining which user inputs correspond to eligible actions for a particular device type. The system determines a device type identifier corresponding to the device that receives the user input and an action to be performed in response to the user input. The system determines that the performed action corresponds to an eligible action type for the device type identifier, and performs further processing using data related to the corresponding user input. Different device type identifiers may be associated with different eligible action types. The system may evaluate multiple user inputs from different users and different devices.

Action eligibility for natural language processing systems

A speech-processing system may provide access to multiple virtual assistants via one or more voice-controlled devices. Each assistant may leverage language processing and language generation features of the speech-processing system, while handling different commands and/or providing access to different back applications. Each assistant may be associated with its own voice and/or speech style, and thus be perceived as having a particular 'personality.' In some situations, a user may invoke a first assistant, e.g., with a wakeword or button press, and provide a command that the speech-processing system may determine will be better handled by a second assistant. The speech-processing system may thus call on a component to generate plan data describing one or more operations for the speech-processing system to execute to handoff the command to the second assistant and provide the user with indications of which assistant will handle the command.

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Seattle, WA, United States of America

Jyoti Chhabra