US 11,113,473 B2Granted

Interpreting expressions having potentially ambiguous meanings in different domains

AssigneeSoundHound, Inc.

InventorsChristopher S. Wilson, Keyvan Mohajer, Bernard Mont-Reynaud

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Abstract

The present invention extends to methods, systems, and computer program products for interpreting expressions having potentially ambiguous meanings in different domains. Multi-domain natural language understanding systems can support a variety of different types of clients. Expressions can be interpreted across multiple domains. Weights can be assigned to domains. Weights can be client specific or expression specific so that a chosen interpretation is more likely correct for the type of client or for its context. Stored weight sets can be chosen according to identifying information carried as metadata with expressions or weight sets carried directly as metadata. Domains can additionally or alternatively be ranked in ordered lists or comparative domain pairs of to favor some domains over others as appropriate for client type or client context.

Claims20

Dependent claims

A method comprising:

providing a configurable platform for natural language understanding for various types of clients:
receiving, at the configurable platform and from developer input into a user interface, instructions to apply, for a client type identifier, a first numerical weight value to a first domain and a second numerical weight value to a second domain;
receiving an expression package containing a natural language expression and the client type identifier;
interpreting the natural language expression according to the first domain to produce a first interpretation and a first score for the first domain;
interpreting the natural language expression according to the second domain to produce a second interpretation and a first score for the second domain;
using the client type identifier to identify the first weight and to identify the second weight;
applying the first numerical weight value to the first score for the first domain to compute a second score for the first domain;
applying the second numerical weight value to the first score for the second domain to compute a second score for the second domain;
selecting the first interpretation as the appropriate interpretation of the natural language expression in view of the second score for the first domain and the second score for the second domain;
and
computing a response to the natural language expression based on selection of the first interpretation.

8 more elements

A method comprising:

receiving a client defined expression package from a client device, the client defined expression package containing a natural language expression, a first numerical weight value, and a second numerical weight value, the first numerical weight value and the second numerical weight value defined to apply to interpretations of the natural language expression in a second domain;
interpreting the natural language expression according to the first domain to produce a first interpretation and a first score for the first domain;
interpreting the natural language expression according to the second domain to produce a second interpretation and a first score for the second domain;
applying the first numerical weight value to the first score for the first domain to compute a second score for the first domain;
applying the second numerical weight value to the first score for the second domain to compute a second score for the second domain;
selecting the first interpretation as the appropriate interpretation of the natural language expression in view of the second score for the first domain and the second score for the second domain;
and
computing a response to the natural language expression based on selection of the first interpretation.

5 more elements

Dependencies are inferred from the claim text.

Facts

Application: 15/942,875Filed 2 Apr 2018
Published: US 2019/0303438 A13 Oct 2019
Granted: 7 Sep 2021
Term ends: Not estimatedThe source records don’t support an estimate.

Classification7 codes

G06F 40/30
Handling natural language data: semantic analysis
G10L 15/1815
Using natural language modelling: semantic context, e.g. disambiguation of the recognition hypotheses based on word meaning
G10L 15/22
Speech recognition: procedures used during a speech recognition process, e.g. man-machine dialogue
G10L 15/30
Constructional details of speech recognition systems: distributed recognition, e.g. in client-server systems, for mobile phones or network…

Family

US 2019/0303438 A1Pre-grant publication · published 3 Oct 2019
US 11,113,473 B2This patent

From the US filing history. Foreign family members aren’t listed.

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