Business listing search

• US 9,460,712 B1
• Filed: 08/07/2014
• Issued: 10/04/2016
• Est. Priority Date: 10/13/2006
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Strope, Brian, Byrne, William J., Beaufays, Francoise
• Primary Examiner(s): MCFADDEN, SUSAN IRIS
• Application Number:
  US14/454,198
• Time in Patent Office: 789 Days
• Field of Search: 704/275
• US Class Current: 1/1
• CPC Class Codes: G06F 16/29 Geographical information databases
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/9537 Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
• CPC Class Codes: G06F 16/9538 Presentation of query results
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G10L 15/18 using natural language modelling
• CPC Class Codes: G10L 15/197 Probabilistic grammars, e.g. word n-grams
• CPC Class Codes: G10L 15/22 Procedures used during a speech recognition process, e.g. man-machine dialogue
• CPC Class Codes: G10L 15/26 Speech to text systems G10L15/08 takes precedence
• CPC Class Codes: G10L 15/30 Distributed recognition, e.g. in client-server systems, for mobile phones or network applications
• CPC Class Codes: G10L 2015/223 Execution procedure of a spoken command
• CPC Class Codes: G10L 2015/228 of application context

Abstract

A method of operating a voice-enabled business directory search system includes receiving category-business pairs, each category-business pair including a business category and a specific business, and establishing a data structure having nodes based on the category-business pairs. Each node of the data structure is associated with one or more business categories and a speech recognition language model for recognizing specific businesses associated with the one or more businesses categories.

Claims

1. A method of searching a business listing with voice commands over the Internet, the method comprising:

receiving, over the Internet, from a user terminal, a query spoken by a user, wherein the query spoken by the user includes a speech utterance representing a category of businesses and a speech utterance representing a geographic location;

recognizing the geographic location with a speech recognition engine based on the speech utterance representing the geographic location;

recognizing the category of businesses with the speech recognition engine based on the speech utterance representing the category of businesses;

searching, with one or more processors, a business listing for businesses within both the recognized category of businesses and the recognized geographic location to select businesses responsive to the query spoken by the user; and

sending to the user terminal information related to at least some of the responsive businesses.

2. The method of claim 1, comprising selecting, from a set of speech recognition language models for recognizing speech, a subset of speech recognition language models, wherein the subset of speech recognition language models is selected based on the recognized location or the recognized category of businesses.

3. The method of claim 2, wherein the set of speech recognition language models includes N-grams in which a probability of a word in a vocabulary is estimated by counting the occurrences of that word in the context of a last N words.

4. The method of claim 2, wherein the set of speech recognition language models includes phrase-list grammars in which a probability of a phrase is estimated by counting the occurrences of the phrase.

5. The method of claim 1, comprising selecting, based on the recognized location, location-specific categories of businesses including the recognized category of businesses.

6. The method of claim 5, comprising selecting a speech recognition language model based on the location-specific categories of businesses, wherein the location specific categories of businesses are arranged in a hierarchical tree of nodes, each node being associated with one or more speech recognition language models, and at least one of the nodes being associated with the selected speech recognition language model.

7. The method of claim 1, comprising:

selecting an adjacent location that is adjacent to the recognized location;

searching the business listing for businesses within both the recognized category of businesses and the adjacent location to select additional businesses responsive to the query spoken by the user; and

sending to the user terminal information related to at least some of the additional businesses.

8. The method of claim 1, comprising:

selecting a broader category of businesses that includes the recognized category of businesses;

searching the business listing for businesses within both the broader category of businesses and the recognized location to select additional businesses responsive to the query spoken by the user; and

sending to the user terminal information related to at least some of the additional businesses.

9. The method of claim 1, wherein the query spoken by the user includes a speech utterance representing a name of a business, the method comprising:

recognizing the name of the business with the speech recognition engine based on the speech utterance representing the name of the business;

searching the business listing for the recognized name of the business.

10. The method of claim 9, wherein recognizing the name of the business with the speech recognition engine includes selecting speech recognition models based on the recognized category of businesses.

11. The method of claim 1, wherein the user terminal is a computer.

12. The method of claim 1, comprising:

obtaining a search log for a search engine, the search log including text queries submitted to the search engine, the text queries including categories of businesses;

constructing a hierarchical tree of the categories of businesses by designating as a root node of the hierarchical tree a node containing all of the categories of businesses;

adding child nodes to the hierarchical tree until entropies of the nodes satisfies a threshold, and

identifying a child node corresponding to the speech utterance representing a category of businesses.

13. A system, comprising:

one or more processors; and

memory storing instructions that when executed by at least some of the one or more processors effectuates operations comprising;

receiving, over the Internet, from a user terminal, a query spoken by a user, wherein the query spoken by the user includes a speech utterance representing a category of businesses and a speech utterance representing a geographic location;

recognizing the geographic location with a speech recognition engine based on the speech utterance representing the geographic location;

recognizing the category of businesses with the speech recognition engine based on the speech utterance representing the category of businesses;

searching a business listing for businesses within both the recognized category of businesses and the recognized geographic location to select businesses responsive to the query spoken by the user; and

sending to the user terminal information related to at least some of the responsive businesses.

14. The system of claim 13, wherein the operations comprise selecting, from a set of speech recognition language models for recognizing speech, a subset of speech recognition language models, wherein the subset of speech recognition language models is selected based on the recognized location or the recognized category of businesses.

15. The system of claim 14, wherein the set of speech recognition language models includes N-grams in which a probability of a word in a vocabulary is estimated by counting the occurrences of that word in the context of a last N words.

16. The system of claim 14, wherein the set of speech recognition language models includes phrase-list grammars in which a probability of a phrase is estimated by counting the occurrences of the phrase.

17. The system of claim 13, wherein the operations comprise selecting, based on the recognized location, location-specific categories of businesses including the recognized category of businesses.

18. The system of claim 17, wherein the operations comprise selecting a speech recognition language model based on the location-specific categories of businesses, wherein the location specific categories of businesses are arranged in a hierarchical tree of nodes, each node being associated with one or more speech recognition language models, and at least one of the nodes being associated with the selected speech recognition language model.

19. The system of claim 13, wherein the operations comprise:

selecting an adjacent location that is adjacent to the recognized location;

searching the business listing for businesses within both the recognized category of businesses and the adjacent location to select additional businesses responsive to the query spoken by the user; and

sending to the user terminal information related to at least some of the additional businesses.

20. The system of claim 13, wherein the operations comprise:

selecting a broader category of businesses that includes the recognized category of businesses;

searching the business listing for businesses within both the broader category of businesses and the recognized location to select additional businesses responsive to the query spoken by the user; and

sending to the user terminal information related to at least some of the additional businesses.

21. The system of claim 13, wherein the query spoken by the user includes a speech utterance representing a name of a business, and wherein the operations further comprise:

recognizing the name of the business with the speech recognition engine based on the speech utterance representing the name of the business;

searching the business listing for the recognized name of the business.

22. The system of claim 21, wherein recognizing the name of the business with the speech recognition engine includes selecting speech recognition models based on the recognized category of businesses.

23. The system of claim 13, wherein the user terminal is a computer.

24. The system of claim 13, wherein the operations comprise:

obtaining a search log for a search engine, the search log including text queries submitted to the search engine, the text queries including categories of businesses;

constructing a hierarchical tree of the categories of businesses by designating as a root node of the hierarchical tree a node containing all of the categories of businesses;

adding child nodes to the hierarchical tree until entropies of the nodes satisfies a threshold, and

identifying a child node corresponding to the speech utterance representing a category of businesses.