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:
Oct. 21, 2025

Filed:

Nov. 17, 2020
Applicant:

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

Inventors:

Lambert Leo Mathias, Seattle, WA (US);

Bala Murali Krishna Ummaneni, Bellevue, WA (US);

Ryan Scott Aldrich, Seattle, WA (US);

Diamond Bishop, Seattle, WA (US);

Ruhi Sarikaya, Redmond, WA (US);

Chetan Nagaraj Naik, Bellevue, WA (US);

Assignee:

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

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G10L 15/18 (2013.01); G06F 16/9032 (2019.01); G06F 40/295 (2020.01); G06F 40/30 (2020.01); G10L 15/22 (2006.01);
U.S. Cl.
CPC ...
G10L 15/1815 (2013.01); G06F 16/90332 (2019.01); G06F 40/295 (2020.01); G06F 40/30 (2020.01); G10L 15/22 (2013.01); G10L 2015/223 (2013.01);
Abstract

A system for processing user utterances and/or text based queries that tracks entities and other context data of a current dialog between the system and the user and can fill slots for new intents of the dialog by performing statistical processing on previously mentioned entities with respect to current slots to be filled. The system may compare a previously mentioned entity to a current slot to be filled using vector representations, such as word embeddings, of the current utterance, dialog history, current intent, name of an entity under consideration, category of the current slot to be filled, distance between the current dialog turn and the dialog turn that mentioned the entity, and other considerations. The individual vectors may be weighted according to an attention operation and processed by a trained decoder to output a score indicating whether the entity in consideration is relevant to the particular slot. In this manner, slots may be filled using entities from previous dialog turns, thus performing statistical anaphora resolution and leading to improved system performance.


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