Voice search engine generating sub-topics based on recognitiion confidence

• US 20070011133A1
• Filed: 06/22/2005
• Published: 01/11/2007
• Est. Priority Date: 06/22/2005
• Status: Abandoned Application

• Current Assignee: Sbc Knowledge Ventures, L.P.
• Original Assignee: Sbc Knowledge Ventures, L.P.
• Inventors: Chang, Hisao
• Application Number:
  US11/158,927
• Publication Number:
  US 20070011133A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G10L 15/26 Speech to text systems G10L15/08 takes precedence
• CPC Class Codes: H04M 3/4938 comprising a voice browser which renders and interprets, e.g. VoiceXML

Abstract

A first utterance of words made by a user is received. A first at least one word in the first utterance is recognized with high confidence. A second at least one word in the first utterance is recognized with less-than-high confidence. A content library is searched for a plurality of items that contain the first at least one word recognized with high confidence. One or more topics, including a first topic, is determined based on the plurality of items. One or more sub-topics associated with the first topic is determined based on the second at least one word recognized with less-than-high confidence. The first topic and the one or more sub-topics are displayed to the user.

Claims

1. A method comprising:

receiving a first utterance of words;

recognizing a first at least one word in the first utterance with high confidence;

recognizing a second at least one word in the first utterance with less-than-high confidence;

searching a content library for a plurality of items that contain the first at least one word recognized with high confidence;

determining one or more topics, including a first topic, based on the plurality of items that contain the first at least one word recognized with high confidence;

determining one or more sub-topics associated with the first topic based on the second at least one word recognized with less-than-high confidence; and

displaying the first topic and the one or more sub-topics.

2. The method of claim 1, further comprising:

storing, in the content library, an associated text-based content summary for each of multiple items;

wherein said searching the content library comprises searching the text-based content summaries.

3. The method of claim 2, wherein the multiple items comprise a plurality of songs, and wherein the associated text-based content summary for each of the songs includes a name of the song, an artist who performed the song, and lyrics of the song.

4. The method of claim 2, further comprising:

for each of a plurality of words, determining an associated word probability based on a frequency of occurrence of the word in the text-based content summaries; and

increasing the associated word probability for each of the words that appear in the text-based content summaries of the plurality of items that contain the first at least one word recognized with high confidence.

5. The method of claim 4, wherein said increasing comprises increasing the associated word probability for a word by a value proportional to a frequency of occurrence of the word in the text-based content summaries of the plurality of items.

6. The method of claim 4, further comprising:

decreasing the associated word probability for each of the words that do not appear in the text-based content summaries of the plurality of items that contain the first at least one word recognized with high confidence.

7. The method of claim 6, wherein said decreasing comprises decreasing, by half, the associated word probability of a word that does not appear in the text-based content summaries of the plurality of items that contain the first at least one word recognized with high confidence.

8. The method of claim 4, further comprising:

receiving a second utterance of words; and

recognizing a third at least one word in the second utterance based on its associated word probability having been increased.

9. The method of claim 1, further comprising:

determining an associated level of search interest for each of a plurality of word phrases.

10. The method of claim 9, wherein said determining the associated level of search interest comprises determining a level of search interest for a word phrase based on a number of search results found for the word phrase in a specific domain.

11. The method of claim 10, wherein the specific domain is a domain of the World Wide Web.

12. The method of claim 9, wherein said determining the one or more topics comprises:

determining a top N of the plurality of items based on at least one word phrase contained therein and its associated level of search interest.

13. The method of claim 1, wherein said determining one or more sub-topics associated with the first topic comprises determining one or more semantic classes tagged to the second at least one word recognized with less-than-high confidence.

14. The method of claim 13, further comprising:

sorting the one or more semantic classes in a domain-specific order.

15. The method of claim 1, wherein the less-than-high confidence is a medium confidence.

16. A computer-readable medium having computer-readable program code to cause a computer system to:

receive a first utterance of words;

recognize a first at least one word in the first utterance with high confidence;

recognize a second at least one word in the first utterance with less-than-high confidence;

search a content library for a plurality of items that contain the first at least one word recognized with high confidence;

determine one or more topics, including a first topic, based on the plurality of items that contain the first at least one word recognized with high confidence;

determine one or more sub-topics associated with the first topic based on the second at least one word recognized with less-than-high confidence; and

display the first topic and the one or more sub-topics.

17. The computer-readable medium of claim 16, wherein the computer-readable program code is to cause the computer system further to:

store, in the content library, an associated text-based content summary for each of multiple items;

wherein the content library is searched by searching the text-based content summaries.

18. The computer-readable medium of claim 17, wherein the multiple items comprise a plurality of songs, and wherein the associated text-based content summary for each of the songs includes a name of the song, an artist who performed the song, and lyrics of the song.

19. The computer-readable medium of claim 17, wherein the computer-readable program code is to cause the computer system further to:

for each of a plurality of words, determine an associated word probability based on a frequency of occurrence of the word in the text-based content summaries; and

increase the associated word probability for each of the words that appear in the text-based content summaries of the plurality of items that contain the first at least one word recognized with high confidence.

20. The computer-readable medium of claim 19, wherein the associated word probability for a word is increased by a value proportional to a frequency of occurrence of the word in the text-based content summaries of the plurality of items.

21. The computer-readable medium of claim 19, wherein the computer-readable program code is to cause the computer system further to:

decrease the associated word probability for each of the words that do not appear in the text-based content summaries of the plurality of items that contain the first at least one word recognized with high confidence.

22. The computer-readable medium of claim 21, wherein the associated word probability of a word that does not appear in the text-based content summaries of the plurality of items that contain the first at least one word recognized with high confidence is decreased by half.

23. The computer-readable medium of claim 19, wherein the computer-readable program code is to cause the computer system further to:

receive a second utterance of words; and

recognize a third at least one word in the second utterance based on its associated word probability having been increased.

24. The computer-readable medium of claim 16, wherein the computer-readable program code is to cause the computer system further to:

determining an associated level of search interest for each of a plurality of word phrases.

25. The computer-readable medium of claim 24, wherein the associated level of search interest is determined by determining a level of search interest for a word phrase based on a number of search results found for the word phrase in a specific domain.

26. The computer-readable medium of claim 25, wherein the specific domain is a domain of the World Wide Web.

27. The computer-readable medium of claim 24, wherein the one or more topics are determined by determining a top N of the plurality of items based on at least one word phrase contained therein and its associated level of search interest.

28. The computer-readable medium of claim 16, wherein the one or more sub-topics associated with the first topic are determined by determining one or more semantic classes tagged to the second at least one word recognized with less-than-high confidence.

29. The computer-readable medium of claim 28, wherein the computer-readable program code is to cause the computer system further to:

sort the one or more semantic classes in a domain-specific order.

30. The computer-readable medium of claim 16, wherein the less-than-high confidence is a medium confidence.