IP Library Granted Patent US 10,140,362
Granted Patent B2
US 10,140,362 · App. 15/231,066 · Granted Nov 27, 2018

Dynamic language model

Inventors: Pedro J. Moreno Mengibar (Jersey City, NJ); Michael H. Cohen (Portola Valley, CA)
Assignee: Google LLC
G06F17/30696G06F17/30241G06F17/30292G06F17/30684G06F17/30687G10L15/005G10L15/14G10L15/197G10L15/24G10L15/26G10L15/265G10L2015/0633G10L2015/081G10L2015/228
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Quick Facts
Patent No.
US 10,140,362
App. No.
15/231,066
Granted
Nov 27, 2018
Kind
B2
Abstract

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for speech recognition. One of the methods includes receiving a base language model for speech recognition including a first word sequence having a base probability value; receiving a voice search query associated with a query context; determining that a customized language model is to be used when the query context satisfies one or more criteria associated with the customized language model; obtaining the customized language model, the customized language model including the first word sequence having an adjusted probability value being the base probability value adjusted according to the query context; and converting the voice search query to a text search query based on one or more probabilities, each of the probabilities corresponding to a word sequence in a group of one or more word sequences, the group including the first word sequence having the adjusted probability value.

Claims (40)

1. A method comprising:

receiving a voice search query, the voice search query provided by a user to a user device;

determining a query context associated with the voice search query;

determining that the query context associated with the voice search query satisfies one or more criteria associated with a particular customized language model of a plurality of customized language models, wherein each customized language model includes one or more adjusted probabilities for respective word sequences of the language model, wherein the probabilities are adjusted with respect to corresponding word sequence probabilities in a base language model;

using the particular customized language model to generate a text search query from the voice search query; and

providing for display on the user device, one or more search results responsive to the text search query.

2. The method of claim 1 , wherein using the particular customized language model includes retrieving the particular customized language model locally from the user device.

3. The method of claim 1 , wherein each customized language model is generated according one or more language adjustment rules for adjusting the respective probabilities of the base language model based on a particular query context.

4. The method of claim 1 , wherein the query context includes a geographic location of the user device.

5. The method of claim 4 , wherein adjusting a probability for the particular customized language model includes adjusting a probability of a particular word sequence based on a degree of relationship between the particular word sequence and the geographic location.

6. The method of claim 5 , wherein:

the particular word sequence includes a name of a feature located at or proximate to the geographic location; and

the degree of relationship is determined based on a distance between the feature and the geographic location in the query context.

7. The method of claim 1 , wherein the query context includes a user provided identifier associated with a social group.

8. The method of claim 7 , wherein adjusting a probability for the particular customized language model includes determining a frequency of occurrence of the word sequence using stored query logs that are associated with the identifier in the social group and adjusting a probability of a particular word sequence based on the frequency.

9. A system comprising:

one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising:

receiving a voice search query, the voice search query provided by a user to a user device;

determining a query context associated with the voice search query;

determining from the query context associated with the voice search query satisfies one or more criteria associated with a particular customized language model of a plurality of customized language models, wherein each customized language model includes one or more adjusted probabilities for respective word sequences of the language model, wherein the probabilities are adjusted with respect to corresponding word sequence probabilities in a base language model;

using the particular customized language model to generate a text search query from the voice search query; and

providing for display on the user device, one or more search results responsive to the text search query.

10. The system of claim 9 , wherein using the particular customized language model includes retrieving the particular customized language model locally from the user device.

11. The system of claim 9 , wherein each customized language model is generated according to one or more language adjustment rules for adjusting the respective probabilities of the base language model based on a particular query context.

12. The system of claim 9 , wherein the query context includes a geographic location of the user device.

13. The system of claim 12 , wherein adjusting a probability for the particular customized language model includes adjusting a probability of a particular word sequence based on a degree of relationship between the particular word sequence and the geographic location.

14. The system of claim 13 , wherein:

the particular word sequence includes a name of a feature located at or proximate to the geographic location; and

the degree of relationship is determined based on a distance between the feature and the geographic location in the query context.

15. The system of claim 9 , wherein the query context includes a user provided identifier associated with a social group.

16. The system of claim 15 , wherein adjusting a probability for the particular customized language model includes determining a frequency of occurrence of the word sequence using stored query logs that are associated with the identifier in the social group and adjusting a probability of a particular word sequence based on the frequency.

17. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that are operable, when executed by data processing apparatus, to cause the data processing apparatus to perform operations comprising:

receiving a voice search query, the voice search query provided by a user to a user device;

determining a query context associated with the voice search query;

determining from the query context associated with the voice search query satisfies one or more criteria associated with a particular customized language model of a plurality of customized language models, wherein each customized language model includes one or more adjusted probabilities for respective word sequences of the language model, wherein the probabilities are adjusted with respect to corresponding word sequence probabilities in a base language model;

using the particular customized language model to generate a text search query from the voice search query; and

providing for display on the user device, one or more search results responsive to the text search query.

18. The computer storage medium of claim 17 , wherein each customized language model is generated according one or more language adjustment rules for adjusting the respective probabilities of the base language model based on a particular query context.

19. The computer storage medium of claim 17 , wherein the query context includes a geographic location of the user device.

20. The computer storage medium of claim 19 , wherein adjusting a probability for the particular customized language model includes adjusting a probability of a particular word sequence based on a degree of relationship between the particular word sequence and the geographic location.

Assignments (2)
CHANGE OF NAME Recorded Oct 5, 2017
From: GOOGLE INC.
To: GOOGLE LLC
Reel/Frame 044129/0001 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 8, 2016
From: MORENO MENGIBAR, PEDRO J.; COHEN, MICHAEL H.
To: GOOGLE INC.
Reel/Frame 039372/0955 →
Continuity (5)
Continuation 15006392 · Jan 26, 2016
Continuation 14719178 · May 21, 2015
Continuation 13802414 · Mar 13, 2013
Provisional Application 61662889 · Jun 21, 2012
Related Publication 20160342682A1 · Nov 24, 2016