The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Nov. 16, 2021

Filed:

May. 01, 2019
Applicant:

Amazon Technologies, Inc., Seattle, WA (US);

Inventors:

Lambert Mathias, Arlington, MA (US);

Ying Shi, Seattle, WA (US);

Imre Attila Kiss, Arlington, MA (US);

Ryan Paul Thomas, Redmond, WA (US);

Frederic Johan Georges Deramat, Seattle, WA (US);

Assignee:

Amazon Technologies, Inc., Seattle, WA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G10L 15/22 (2006.01); G10L 15/26 (2006.01); G06F 40/35 (2020.01); G06F 40/40 (2020.01); G06F 40/56 (2020.01); G06F 40/284 (2020.01); G06F 40/295 (2020.01); G10L 13/08 (2013.01);
U.S. Cl.
CPC ...
G10L 15/22 (2013.01); G06F 40/284 (2020.01); G06F 40/295 (2020.01); G06F 40/35 (2020.01); G06F 40/40 (2020.01); G06F 40/56 (2020.01); G10L 13/08 (2013.01); G10L 15/26 (2013.01);
Abstract

Features are disclosed for processing a user utterance with respect to multiple subject matters or domains, and for selecting a likely result from a particular domain with which to respond to the utterance or otherwise take action. A user utterance may be transcribed by an automatic speech recognition ('ASR') module, and the results may be provided to a multi-domain natural language understanding ('NLU') engine. The multi-domain NLU engine may process the transcription(s) in multiple individual domains rather than in a single domain. In some cases, the transcription(s) may be processed in multiple individual domains in parallel or substantially simultaneously. In addition, hints may be generated based on previous user interactions and other data. The ASR module, multi-domain NLU engine, and other components of a spoken language processing system may use the hints to more efficiently process input or more accurately generate output.


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