TEMPLATE CONCATENATION FOR CAPTURING MULTIPLE CONCEPTS IN A VOICE QUERY

• US 20110314003A1
• Filed: 06/17/2010
• Published: 12/22/2011
• Est. Priority Date: 06/17/2010
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Ju, Yun-Cheng, Wang, Ye-Yi, Li, Xiao, Wu, Wei
• Application Number:
  US12/817,233
• Publication Number:
  US 20110314003A1
• Time in Patent Office: Days
• US Class Current: 707/723
• CPC Class Codes: G06F 16/3329 Natural language query formulation or dialogue systems
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G10L 15/06 Creation of reference templates; Training of speech recognition systems, e.g. adaptation to the characteristics of the speaker's voice G10L15/14 takes precedence
• CPC Class Codes: G10L 15/1822 Parsing for meaning understanding

Abstract

Architecture that provides the capability to identify which parts (terms and phrases) of a voice query have been covered by predefined phrase templates, and then to concatenate matching phrase templates into a new paraphrased query. A match-drop-continue algorithm is disclosed that progressively masks out the portions (phrases, terms) of the query matched to the phrase templates. Ultimately, the matched phrase templates are accumulated and organized together dynamically into a rephrased version of the original voice query. A user interface is provided that allows the user to confirm/summarize the multiple concepts in a progressive manner.

Claims

1. A computer-implemented system that processes voice input into text, the system having computer readable media that store executable instructions executed by a processor, comprising:

a query processing component that applies a paraphrase algorithm progressively on terms of a voiced query according to predefined phrase templates; and

a concatenation component that dynamically concatenates matched phrase templates to create a rephrased version of the query.

2. The system of claim 1, wherein the paraphrase algorithm performs paraphrase detection on the voiced query for terms that match a phrase template.

3. The system of claim 2, wherein the paraphrase algorithm removes terms from the query which match a phrase template.

4. The system of claim 3, wherein the paraphrase algorithm progressively updates the query based on the removed terms for continued paraphrase processing until completed.

5. The system of claim 1, wherein the paraphrase algorithm employs an n-gram translation model for paraphrase detection.

6. The system of claim 1, wherein the paraphrase algorithm employs a logistic regression model for paraphrase detection.

7. The system of claim 1, wherein the query processing component and the concatenation component are part of a mobile communications system that processes the voiced query as a message.

8. The system of claim 1, wherein the query processing component employs a message edit distance alignment algorithm to analyze a semantic structure of the voiced query.

9. The system of claim 1, further comprising a user interface that presents summarization and confirmation of multiple concepts of the voiced query in a progressive manner.

10. A computer-implemented method executed by a processor to process voice input into text, comprising:

detecting a concept in a voiced query using a paraphrase algorithm;

comparing the concept to predefined phrase templates;

selecting a matching phrase template;

removing terms of the concept from the query;

processing remaining terms in the query for other concepts and matching phrase templates; and

creating rephrased queries based on concatenation of the matching phrase templates.

11. The method of claim 10, further comprising presenting a ranked set of the rephrased queries for selection and transmission.

12. The method of claim 10, further comprising detecting the concepts by paraphrase detection based on an n-gram translation model that employs a model trained on paraphrase template pairs and an anti-model trained on non-paraphrase template pairs.

13. The method of claim 10, further comprising detecting the concepts by paraphrase detection based on a logistic regression model.

14. The method of claim 13, further comprising extracting at least one of a word pair n-gram feature, identical word pair ratio feature, or part-of-message discrepancy feature for logistic regression-based paraphrase detection.

15. The method of claim 10, further comprising performing edit distance alignment that categorizes terms in the query according to semantic types.

16. A computer-implemented method executed by a processor to process voice input into text, comprising:

detecting a concept in a voiced query using a paraphrase algorithm;

comparing the concept to predefined phrase templates;

selecting a matching phrase template;

removing terms of the concept from the query;

progressively processing remaining terms in the query for other concepts and matching phrase templates;

creating rephrased queries based on concatenation of the matching phrase templates; and

presenting a ranked set of the rephrased queries for selection and transmission.

17. The method of claim 16, further comprising detecting the concepts by paraphrase detection based on an n-gram translation model that employs a model trained on paraphrase template pairs and an anti-model trained on non-paraphrase template pairs.

18. The method of claim 16, further comprising extracting at least one of a word pair n-gram feature, an identical word pair ratio feature, or part-of-message discrepancy feature for logistic regression as part of paraphrase detection.

19. The method of claim 16, further comprising performing edit distance alignment that categorizes terms in the query according to semantic types.

20. The method of claim 16, further comprising analyzing semantic structure of the voiced query based on a message edit distance alignment algorithm.