System and method of providing a spoken dialog interface to a website

• US 8,688,456 B2
• Filed: 05/10/2013
• Issued: 04/01/2014
• Est. Priority Date: 12/18/2002
• Status: Expired due to Term

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: AT&T Intellectual Property I LP (AT&T, Inc.)
• Inventors: Bangalore, Srinivas, Feng, Junlan, Rahim, Mazin G.
• Primary Examiner(s): YEN, ERIC L
• Application Number:
  US13/891,447
• Publication Number:
  US 20130246069A1
• Time in Patent Office: 326 Days
• Field of Search: 704/9, 704270-275
• US Class Current: 704/270.1
• CPC Class Codes: G10L 13/08 Text analysis or generation of parameters for speech synthesis out of text, e.g. grapheme to phoneme translation, prosody generation or stress or intonation determination
• CPC Class Codes: G10L 15/063 Training
• CPC Class Codes: G10L 15/183 using context dependencies, e.g. language models
• CPC Class Codes: G10L 15/22 Procedures used during a speech recognition process, e.g. man-machine dialogue
• CPC Class Codes: H04M 3/4936 Speech interaction details speech recognition per se G10L15/00

Abstract

Disclosed is a method for training a spoken dialog service component from website data. Spoken dialog service components typically include an automatic speech recognition module, a language understanding module, a dialog management module, a language generation module and a text-to-speech module. The method includes selecting anchor texts within a website based on a term density, weighting those anchor texts based on a percent of salient words to total words, and incorporating the weighted anchor texts into a live spoken dialog interface, the weights determining a level of incorporation into the live spoken dialog interface.

Claims

1. A method comprising:

selecting an anchor text in a website based on a term density;

weighting the anchor text with a weight based on a ratio of salient words to total words, to yield a weighted anchor text; and

incorporating the weighted anchor text into a live spoken dialog system, the spoken dialog system engaging in a spoken dialog with a user, wherein the weight determines a level of incorporation of the weighted anchor text into the live spoken dialog.

2. The method of claim 1, further comprising extracting from the website a linguistic item wherein the level of incorporation is further based on the linguistic item.

3. The method of claim 2, further comprising:

generating a website specific language model using the linguistic item and the weighted anchor text.

4. The method of claim 3, further comprising:

integrating the website specific language model into the live spoken dialog.

5. The method of claim 2, wherein the linguistic item comprises one of a named-entity, a nominal phrase, a verbal phrase, and an adjectival phrase.

6. The method of claim 1, further comprising:

computing an alias comprising a best representative anchor text from a plurality of weighted anchor texts.

7. The method of claim 6, wherein the best representative anchor text has a weight associated with a highest ratio of salient words to total words from the plurality of weighted anchor texts.

8. A system comprising:

a processor; and

a computer-readable storage medium having instructions stored which, when executed by the processor, result in the processor performing operations comprising;

selecting an anchor text in a website based on a term density;

weighting the anchor text with a weight based on a ratio of salient words to total words, to yield a weighted anchor text; and

incorporating the weighted anchor text into a live spoken dialog system, the spoken dialog system engaging in a spoken dialog with a user, wherein the weight determines a level of incorporation of the weighted anchor text into the live spoken dialog.

9. The system of claim 8, the computer-readable storage medium having additional instructions stored which result in the operations further comprising extracting from the website a linguistic item wherein the level of incorporation is further based on the linguistic item.

10. The system of claim 9, the computer-readable storage medium having further instructions stored which result in the operations further comprising:

generating a website specific language model using the linguistic item and the weighted anchor text.

11. The system of claim 10, the computer-readable storage medium having yet additional instructions stored which result in the operations further comprising:

integrating the website specific language model into the live spoken dialog.

12. The system of claim 9, wherein the linguistic item comprises one of a named-entity, a nominal phrase, a verbal phrase, and an adjectival phrase.

13. The system of claim 9, the computer-readable storage medium having further instructions stored which result in the operations further comprising:

computing an alias comprising a best representative anchor text from a plurality of weighted anchor texts.

14. The system of claim 13, wherein the best representative anchor text has a weight associated with a highest ratio of salient words to total words from the plurality of weighted anchor texts.

15. A computer-readable storage medium device having instructions stored which, when executed by a computing device, result in the computing device performing operations comprising:

selecting an anchor text in a website based on a term density;

weighting the anchor text with a weight based on a ratio of salient words to total words, to yield a weighted anchor text; and

incorporating the weighted anchor text into a live spoken dialog system, the spoken dialog system engaging in a spoken dialog with a user, wherein the weight determines a level of incorporation of the weighted anchor text into the live spoken dialog.

16. The computer-readable storage device of claim 15, the computer-readable storage device having additional instructions stored which result in the operations further comprising extracting from the website a linguistic item wherein the level of incorporation is further based on the linguistic item.

17. The computer-readable storage device of claim 16, the computer-readable storage device having further instructions stored which result in the operations further comprising:

generating a website specific language model using the linguistic item and the weighted anchor text.

18. The computer-readable storage device of claim 17, the computer-readable storage device having yet additional instructions stored which result in the operations further comprising:

integrating the website specific language model into the live spoken dialog.

19. The computer-readable storage device of claim 16, wherein the linguistic item comprises one of a named-entity, a nominal phrase, a verbal phrase, and an adjectival phrase.

20. The computer-readable storage device of claim 15, the computer-readable storage device having further instructions stored which result in the operations further comprising:

computing an alias comprising a best representative anchor text from a plurality of weighted anchor texts.