IP Library Granted Patent US 8,831,930
Granted Patent B2
US 8,831,930 · App. 12/913,151 · Granted Sep 9, 2014

Business listing search

Inventors: Brian Strope (Palo Alto, CA); William J. Byrne (Davis, CA); Francoise Beaufays (Mountain View, CA)
Assignee: Google Inc.
G10L15/26G06Q30/02
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Quick Facts
Patent No.
US 8,831,930
App. No.
12/913,151
Granted
Sep 9, 2014
Kind
B2
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 (24)

1. A method comprising:

collecting, by one or more processors, information about associations of specific businesses with categories from keyword searches;

establishing, by the one or more processors, speech recognition language models based on the information, each language model being associated with one or more categories, each language model for recognizing specific businesses associated with the one or more categories; and

recognizing, by the one or more processors, specific businesses in a speech utterances using the language models.

2. The method of claim 1 , further comprising establishing, by the one or more processors, a hierarchical tree having nodes, each node being associated with one or more of the categories and one of the speech recognition language models.

3. The method of claim 1 wherein the keyword searches comprise at least one of web searches, intranet searches, and desktop searches.

4. A method comprising:

receiving, by one or more processors, a speech input having information about a business category and an identifier of a specific business;

mapping, by the one or more processors, the type of business in the speech input to nodes in a data structure, each node being associated with one or more business categories and a speech recognition language model; and

recognizing, by the one or more processors, the identifier of the specific business using one or more language models determined based on the mapping.

5. The method of claim 4 wherein the mapping comprises, for each of some of the nodes, determining a similarity score representing a similarity between the business category in the speech input and the one or more business categories associated with the node.

6. The method of claim 5 , further comprising generating, by the one or more processors, weights for the language models based on the similarity scores.

7. The method of claim 4 , further comprising finding, by the one or more processors, a particular node having a highest similarity to the business category in the speech input, and using a first language model associated with the particular node and a second language model associated with a parent node of the particular node to recognize the identifier.

8. An apparatus comprising:

a voice-enabled user interface to receive a speech input having information about a business category and an identifier of a specific business;

a mapping module to compare the business category to a plurality of nodes of a data structure, each node being associated with one or more business categories and a speech recognition language model; and

a speech recognition module to recognize the identifier of the specific business using one or more language models determined based on the mapping.

9. The apparatus of claim 8 wherein the mapping module determines, for each of some of the nodes, a similarity score between the business category in the speech input and the one or more business categories associated with the node.

10. The apparatus of claim 8 wherein the mapping module generates weights for the one or more language models based on the similarity scores.

11. The apparatus of claim 8 wherein the mapping module finds a particular node having a highest similarity to the business category in the speech input, and uses a first language model associated with the particular node and a second language model associated with a parent node of the particular node to recognize the identifier.

12. An apparatus comprising:

means for mapping information about a business category to a plurality of nodes of a hierarchical tree and generating weight values for the nodes, each node being associated with one or more business categories and a language model for recognizing specific businesses associated with the one or more business categories; and

a speech recognition engine to recognize a specific business in a speech input using one or more language models determined based on the mapping.

13. The apparatus of claim 12 wherein the mapping means determines weight values for the nodes based on the mapping, and the one or more language models are weighted by the weight values.

Assignments (2)
CHANGE OF NAME Recorded Oct 2, 2017
From: GOOGLE INC.
To: GOOGLE LLC
Reel/Frame 044277/0001 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 24, 2011
From: STROPE, BRIAN; BYRNE, WILLIAM J.; BEAUFAYS, FRANCOISE
To: GOOGLE INC.
Reel/Frame 025860/0891 →
Continuity (2)
Division 11549484 · Oct 13, 2006
Related Publication 20110047139A1 · Feb 24, 2011