Claims
- 1. A method for providing a spoken language interface to an information database, comprising:
generating a grammars database based on the entries contained in the information database, wherein entries in the grammars database are a compact representation of the entries in the information database; generating an index database based on the entries contained in the information database; periodically updating the grammars database based on updated entries contained in the information database; periodically updating the index database based on the updated entries contained in the information database; generating a recognized result of a user's communication based on the updated grammars database; searching the updated index database for a list of matching entries that match the recognized result; and outputting the list of matching entries.
- 2. The method of claim 1, wherein generating the grammars database comprises:
generating entries in the grammars database based on the entries in the information database using estimated N-gram statistics.
- 3. The method of claim 2, wherein entries in the grammars database include bi-gram grammars.
- 4. The method of claim 1, wherein periodically updating the grammars database comprises:
generating entries in the grammars database based on the entries in the information database using estimated N-gram statistics.
- 5. The method of claim 1, wherein the entries in the grammars database do not directly correspond to entries in the listings database.
- 6. The method of claim 1, wherein the information database is a listings database.
- 7. The method of claim 1, wherein the grammars database is updated daily, weekly or monthly.
- 8. The method of claim 1, wherein the index database is updated daily, weekly or monthly.
- 9. The method of claim 1, wherein periodically updating the grammars database comprises:
processing a plurality of entries of the information database through a distortion model.
- 10. The method of claim 9, further comprising:
generating a transformation rule set for each entry from the plurality of entries; and transforming each entry into a variation of the entry based on the rule set.
- 11. The method of claim 10, furthering comprising:
generating a probability associated with the variation of the entry.
- 12. The method of claim 11, further comprising:
creating a pseudo corpus including the variation and the associated probability.
- 13. The method of claim 11, further comprising:
generating a language model based on the variation and the associated probability using parameter estimation.
- 14. The method of claim 1, further comprising:
searching the listing database for the list of matching entries that matched the recognized result based on the updated index database.
- 15. The method of claim 1, wherein periodically updating the index database comprises:
processing a plurality of entries of the information database through a distortion model.
- 16. The method of claim 15, further comprising:
generating a transformation rule set for each entry from the plurality of entries; and transforming each entry into a variation of the entry based on the rule set.
- 17. The method of claim 16, furthering comprising:
generating a probability associated with the variation of the entry.
- 18. A method comprising:
retrieving each entry of a plurality of entries contained in an informational database; applying a transformation rule to each entry of the plurality of entries in the informational database; generating a variation of each entry based on the applied transformation rule; generating an associated probability for each variation; and generating a stochastic language model for each variation and the associated probability based a parameter estimation technique.
- 19. The method of claim 18, wherein the informational database is a listings database.
- 20. The method of claim 18, wherein the variation of an entry is a distortion of the entry in the informational database.
- 21. The method of claim 18, further comprising:
outputting the generated stochastic language model into a grammar database.
- 22. The method of claim 18, further comprising:
outputting the generated stochastic language model into an index database.
- 23. The method of claim 18, wherein the transformation rule specify an alternate way of uttering an entry.
- 24. The method of claim 23, further comprising:
generating a pseudo corpus based on each variation and the associated probability.
- 25. The method of claim 18, wherein the variation includes an alternate word sequence representing an entry in the informational database.
- 26. An apparatus for providing a spoken language interface to an information database, comprising:
a grammar generator that is to periodically update a grammars database based on updated entries contained in an information database, wherein entries in the grammars database are a compact representation of the entries in the information database; a index generator that is to periodically update an index database based on the updated entries contained in the information database; a recognizer that is to generating a recognized result of a user's communication based on the updated grammars database; a matcher that is to search the updated index database for a list of matching entries that match the recognized result; and an output manager to output the list of matching entries.
- 27. The apparatus of claim 26, wherein the grammar database is to periodically update entries in the grammars database based on the entries in the information database based on estimated N-gram statistics.
- 28. The apparatus of claim 26, wherein the entries in the grammars database do not directly correspond to entries in the listings database.
- 29. The apparatus of claim 26, wherein the grammar generator comprises:
a distortion model that is to generate a variation of an entry in the information database.
- 30. The apparatus of claim 29, wherein the distortion model comprises:
an analyzer that is to generate a transformation rule; and an orthographies generator that is to generate the variation of the entry in the information database based on the generated transformation rule.
- 31. The apparatus of claim 30, wherein the distortion model to generate a probability associated with the variation.
- 32. The apparatus of claim 31, further comprising:
a pseudo corpus that is to store the variation and the associated probability.
- 33. The apparatus of claim 31, further comprising:
a parameter estimator that is to generate a language model based on the variation and the associated probability.
- 34. A machine-readable medium having stored thereon a plurality of executable instructions, the plurality of instructions comprising instructions to:
generate a grammars database based on the entries contained in the information database, wherein entries in the grammars database are a compact representation of the entries in the information database; generate an index database based on the entries contained in the information database; periodically update the grammars database based on updated entries contained in the information database; periodically update the index database based on the updated entries contained in the information database; generate a recognized result of a user's communication based on the updated grammars database; search the updated index database for a list of matching entries that match the recognized result; and output the list of matching entries.
- 35. The machine-readable medium of claim 34 having stored thereon additional executable instructions, the additional instructions comprising instructions to:
generate entries in the grammars database based on the entries in the information database using estimated N-gram statistics.
- 36. The machine-readable medium of claim 34 having stored thereon additional executable instructions, the additional instructions comprising instructions to:
generate entries in the grammars database based on the entries in the information database using estimated N-gram statistics.
- 37. The machine-readable medium of claim 34 having stored thereon additional executable instructions, the additional instructions comprising instructions to:
process a plurality of entries of the information database through a distortion model.
- 38. The machine-readable medium of claim 37 having stored thereon additional executable instructions, the additional instructions comprising instructions to:
generate a transformation rule set for each entry from the plurality of entries; and transform each entry into a variation of the entry based on the rule set.
- 39. The machine-readable medium of claim 38 having stored thereon additional executable instructions, the additional instructions comprising instructions to:
generate a probability associated with the variation of the entry.
- 40. The machine-readable medium of claim 39 having stored thereon additional executable instructions, the additional instructions comprising instructions to:
create a pseudo corpus including the variation and the associated probability.
- 41. The machine-readable medium of claim 39 having stored thereon additional executable instructions, the additional instructions comprising instructions to:
generate a language model based on the variation and the associated probability using parameter estimation.
- 42. The machine-readable medium of claim 34 having stored thereon additional executable instructions, the additional instructions comprising instructions to:
search the listing database for the list of matching entries that matched the recognized result based on the updated index database.
- 43. The machine-readable medium of claim 34 having stored thereon additional executable instructions, the additional instructions comprising instructions to:
process a plurality of entries of the information database through a distortion model.
- 44. The machine-readable medium of claim 43 having stored thereon additional executable instructions, the additional instructions comprising instructions to:
generate a transformation rule set for each entry from the plurality of entries; and transform each entry into a variation of the entry based on the rule set.
CROSS-REFERENCE TO RELATED PATENT APPLICATIONS
[0001] This patent application claims the benefit of, and incorporates by reference, each of: U.S. Provisional Patent Application Serial No. 60/343,597, U.S. Provisional Patent Application Serial No. 60/343,588, U.S. Provisional Patent Application Serial No. 60/343,590, U.S. Provisional Patent Application Serial No. 60/343,595, U.S. Provisional Patent Application Serial No. 60/343,596; U.S. Provisional Patent Application Serial No. 60/343,593, U.S. Provisional Patent Application Serial No. 60/343,592, U.S. Provisional Patent Application Serial No. 60/343,589, and U.S. Provisional Patent Application Serial No. 60/343,591, all filed Jan. 2, 2002.
Provisional Applications (9)
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Number |
Date |
Country |
|
60343597 |
Jan 2002 |
US |
|
60343588 |
Jan 2002 |
US |
|
60343590 |
Jan 2002 |
US |
|
60343595 |
Jan 2002 |
US |
|
60343596 |
Jan 2002 |
US |
|
60343593 |
Jan 2002 |
US |
|
60343592 |
Jan 2002 |
US |
|
60343589 |
Jan 2002 |
US |
|
60343591 |
Jan 2002 |
US |