Dynamic language model

• US 10,140,362 B2
• Filed: 08/08/2016
• Issued: 11/27/2018
• Est. Priority Date: 06/21/2012
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google LLC (Alphabet Inc.)
• Inventors: Moreno Mengibar, Pedro J., Cohen, Michael H.
• Primary Examiner(s): Baker, Charlotte M
• Application Number:
  US15/231,066
• Publication Number:
  US 20160342682A1
• Time in Patent Office: 841 Days
• Field of Search: 382100, 704 9, 704E15022, 704275, 704235, 704236, 704249, 704251, 704252, 704253, 704257, 704276, 707707, 707723, 707752, 707769, 379 8801, 379 8822, 715728
• CPC Class Codes: G06F 16/211 Schema design and management
• CPC Class Codes: G06F 16/29 Geographical information databases
• CPC Class Codes: G06F 16/3329 Natural language query formulation or dialogue systems
• CPC Class Codes: G06F 16/3344 using natural language analysis
• CPC Class Codes: G06F 16/3346 using probabilistic model
• CPC Class Codes: G06F 16/338 Presentation of query results
• CPC Class Codes: G06F 16/387 using geographical or spatial information, e.g. location
• CPC Class Codes: G10L 15/005 Language recognition
• CPC Class Codes: G10L 15/14 using statistical models, e.g. Hidden Markov Models [HMMs] G10L15/18 takes precedence
• CPC Class Codes: G10L 15/197 Probabilistic grammars, e.g. word n-grams
• CPC Class Codes: G10L 15/24 Speech recognition using non-acoustical features
• CPC Class Codes: G10L 15/26 Speech to text systems G10L15/08 takes precedence
• CPC Class Codes: G10L 2015/0633 using lexical or orthographic knowledge sources
• CPC Class Codes: G10L 2015/081 Search algorithms, e.g. Baum-Welch or Viterbi
• CPC Class Codes: G10L 2015/228 of application context

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

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.