Amazon Technologies, Inc.

Shemyla Anwar

Vikram Kumar Gundeti

Michael F Schwartz

Rongzhou Shen

Bo Li

Leopold Bushkin

Munir Mahmood

Yaser Khan

Alexander Thomas Loeb

Mohammed Arif

Edward Page Foyle

Sylvester-Jaron Dewey Ogletree

Rujie Yao

Raveendra Kulakarni

Xu Han

Techniques for a natural language processing (NLP) system to implement more than one assistant are described. The NLP system may receive a natural language input corresponding to more than one user command. The NLP system may respond to a first command, of the natural language input, using a TTS voice of a first NLP system assistant. The NLP system may respond to a second command, of the natural language input, using a TTS voice of a second NLP system assistant.

Multi-assistant natural language input processing

Techniques for responding to a user input using a device-executable intent are described. A user may speak, to a device, an input corresponding to a first natural language understanding (NLU) intent executable by a speech processing system. The speech processing system may determine a device type corresponding to the device and, based on the device type, determine a data subscription is required to execute the first NLU intent. Thereafter, the speech processing system may determine a second NLU intent that is executable by the device and that results in the output of similar content to the execution of the first NLU intent. The speech processing system then directs the device to execute the second NLU intent.

Natural language understanding intent adjustment

Techniques for a natural language processing (NLP) system to implement more than one assistant are described. The NLP system may receive a natural language input from a device. The NLP system may also receive one or more signals representing one or more assistants to be implemented with respect to the natural language input. The NLP system may intelligently select an assistant to be invoked with respect to the natural language input. Once the assistant is selected, the NLP system may cause content, output to a user, to have characteristics specific to the assistant.

Multi-assistant natural language input processing to determine a voice model for synthesized speech

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Bothell, WA, United States of America

Shemyla Anwar