Telephone directory information retrieval system and method

• US 20040186819A1
• Filed: 03/18/2003
• Published: 09/23/2004
• Est. Priority Date: 03/18/2003
• Status: Abandoned Application

• Current Assignee: Aurilab LLC
• Original Assignee: Aurilab LLC
• Inventors: Baker, James K.
• Application Number:
  US10/389,750
• Publication Number:
  US 20040186819A1
• Time in Patent Office: Days
• US Class Current: 707/1
• CPC Class Codes: G10L 15/22 Procedures used during a speech recognition process, e.g. man-machine dialogue
• CPC Class Codes: H04M 2201/40 using speech recognition speech recognition per se G10L15/00
• CPC Class Codes: H04M 2203/251 where a voice mode or a visual mode can be used interchangeably
• CPC Class Codes: H04M 3/4931 Directory assistance systems

Abstract

A database retrieval system obtains telephone directory information, and includes a speech receiving unit that outputs an acoustic observation sequence corresponding to a speaker'"'"'s utterance of a first name and last name of someone for whom a telephone number is desired. The system also includes a speech recognition processing unit that performs speech recognition processing on acoustic observations, to obtain a list of candidate hypotheses, and to obtain a match score for each candidate hypothesis. The system further includes a hypothesis evaluating unit that determines whether any candidate hypothesis has an initial for a first name part of the corresponding database entry, to generate all consistent first names, and to obtain a plurality of generated hypotheses corresponding to each of the generated first names. The speech recognition processing unit performs another speech recognition processing on the acoustic observation sequence, to obtain a match score for each generated hypothesis. The hypothesis evaluation unit updates a match score for each candidate hypothesis to a highest match score of the corresponding ones of the generated hypotheses, and a best scoring candidate hypothesis is used to obtain information from a database.

Claims

1. A method for obtaining telephone directory information from a database, comprising:

a) performing a first speech recognition processing on a speaker'"'"'s utterance, in order to obtain a list of candidate hypotheses that have corresponding database entries in the database;

b) determining whether or not any of the list of candidate hypotheses has an initial, abbreviation or nickname for a part of the corresponding database entry;

c) if the determination in step b) is that at least one of the list of candidate hypotheses has an initial, abbreviation or nickname for the part, then performing the following steps for that candidate hypothesis;

d) generating at least one substitution consistent with the initial, abbreviation or nickname, and obtaining at least one generated hypothesis that includes the generated substitution;

e) performing a second speech recognition processing for the sequence of acoustic observations with respect to the at least one generated hypothesis, and obtaining a match score for each of the at least one generated hypotheses with respect to the caller'"'"'s utterance; and

f) determining a highest match score of the list of candidate hypotheses as a recognized answer to be utilized to retrieve the telephone directory information from the database, wherein the match score of the at least one generated hypothesis is used instead of the match score of its corresponding candidate hypothesis if the match score of the generated hypothesis is greater than the match score of its corresponding candidate hypothesis.

2. The method according to claim 1, further comprising:

if the determination in step b) is that none of the list of candidate hypotheses has an initial, abbreviation or nickname for the part, then determining one of the list of candidate hypotheses having a highest matching score as a recognized answer, which is used to retrieve the telephone directory information from the database.

3. The method according to claim 1, wherein a plurality of generated hypotheses are obtained in step d), and correspond to an expanded grammar utilized in the second speech recognition processing.

4. The method according to claim 1, wherein the second speech recognition processing is performed with an expanded grammar by expanding at least one field of entries stored in the database, based on corresponding information in the at least one field of entries as obtained from the list of candidate hypotheses.

5. The method according to claim 1, wherein the second speech recognition processing performed in step e). is performed using a grammar different than what is used by the first speech recognition processing performed in step a).

6. The method according to claim 1, further comprising:

if there are at least two of the candidate hypotheses that exceed a predetermined match score value, or none of the candidate hypotheses exceed the predetermined match score, then requesting additional information from the speaker with regards to the person for whom the, speaker desires to be provided with a telephone number; and

performing the second speech recognition processing using an expanded grammar that includes the additional information.

7. The method according to claim 1, wherein the sequence of acoustic observations corresponds to a sequence of phonemes.

8. The method according to claim 1, wherein the sequence of acoustic observations corresponds to a sequence of words.

9. The method according to claim 1, wherein the substitutions generated in step d) are obtained from information stored in the database.

10. The method according to claim 1, wherein the part of the candidate database entry is a first name.

11. The method according to claim 3, further comprising:

creating a grammar for a field entry from the list of candidate hypotheses.

12. The method according to claim 4, further comprising:

creating a grammar for a field entry from the list of candidate hypotheses.

13. The method according to claim 5, further comprising:

creating a grammar for a field entry from the list of candidate hypotheses, by selecting from the telephone directory for the corresponding field an entry that is consistent with the initial, abbreviation or nickname.

14. A system for obtaining telephone directory information from a database, comprising:

a speech recognition processing unit configured to perform a first speech recognition processing on a speaker'"'"'s utterance, in order to obtain a list of candidate hypotheses that have corresponding database entries in the database; and

a hypothesis evaluation unit configured to determine whether or not any of the list of candidate hypotheses output by the speech recognition processing unit has an initial, abbreviation or nickname for a part of the corresponding database entry,

wherein, when the determination by the hypothesis evaluation unit is that at least one of the list of candidate hypotheses has an initial, abbreviation or nickname for the part, then the hypothesis evaluation unit generates at least one substitution consistent with the initial, abbreviation or nickname, and obtains at least one generated hypothesis that includes the generated substitution,

wherein the speech recognition processing unit performs a second speech recognition processing for the sequence of acoustic observations with respect to the at least one generated hypothesis provided to the speech recognition processing unit by the hypothesis evaluation unit, and wherein a match score is obtained for each of the at least one generated hypotheses with respect to the caller'"'"'s utterance,

wherein a highest match score of the list of candidate hypotheses is determined to be a recognized answer that is utilized to retrieve the telephone directory information from the database, and

wherein the match score of the at least one generated hypothesis is used instead of the match score of its corresponding candidate hypothesis if the match score of the generated hypothesis is greater than the match score of its corresponding candidate hypothesis.

15. The system according to claim 14, wherein,

when the determination by the hypothesis evaluation unit is that none of the list of candidate hypotheses has an initial, abbreviation or nickname for the first name part, then one of the list of candidate hypotheses having a highest matching score is determined to be a recognized answer, which is utilized to retrieve the telephone directory information from the database.

16. The system according to claim 14, wherein a plurality of generated hypotheses are obtained by the hypothesis evaluation unit, and correspond to an expanded grammar utilized in the second speech recognition processing.

17. The system according to claim 14, wherein the second speech recognition processing is performed with an expanded grammar by expanding at least one field of entries stored in the database, based on corresponding information in the at least one field of entries as obtained from the list of candidate hypotheses.

18. The system according to claim 14, wherein the second speech recognition processing is performed using a grammar different than what is used by the first speech recognition processing.

19. The system according to claim 14, further comprising:

an additional information requesting unit,

wherein, if there are at least two of the candidate hypotheses that exceed a predetermined match score value, or none of the candidate hypotheses exceed the predetermined match score, then the additional information requesting unit requests additional information from the speaker with regards to the person for whom the speaker desires to be provided with a telephone number,

wherein the second speech recognition processing is performed by the speech recognition processing unit, using an expanded grammar that includes the additional information.

20. The system according to claim 14, wherein the sequence of acoustic observations corresponds to a sequence of phonemes.

21. The system according to claim 14, wherein the sequence of acoustic observations corresponds to a sequence of words.

22. The system according to claim 14, wherein the substitutions generated by the hypothesis evaluation unit are obtained from information stored in the database.

23. The system according to claim 14, wherein the part of the corresponding database entry is a first name.

33. The program product according to claim 19, wherein the part of the corresponding database entry is a first name.

24. A program product having machine readable code for obtaining telephone directory information from a database, the program code, when executed, causing a machine to perform the following steps:

a) performing a first speech recognition processing on a speaker'"'"'s utterance, in order to obtain a list of candidate hypotheses that have corresponding database entries in the database;

b) determining whether or not any of the list of candidate hypotheses has an initial, abbreviation or nickname for a part of the corresponding database entry;

c) if the determination in step b) is that at least one of the list of candidate hypotheses has an initial, abbreviation or nickname for the part, then performing the following steps for that candidate hypothesis;

d) generating at least one substitution consistent with the initial, abbreviation or nickname, and obtaining at least one generated hypothesis that includes the generated substitution;

e) performing a second speech recognition processing for the sequence of acoustic observations with respect to the at least one generated hypothesis, and obtaining a match score for each of the at least one generated hypotheses with respect to the caller'"'"'s utterance; and

f) determining a highest match score of the list of candidate hypotheses as a recognized answer to be utilized to retrieve the telephone directory information from the database, wherein the match score of the at least one generated hypothesis is used instead of the match score of its corresponding candidate hypothesis if the match score of the generated hypothesis is greater than the match score of its corresponding candidate hypothesis.

25. The program product according to claim 24, further comprising:

if the determination in step b) is that none of the list of candidate hypotheses has an initial, abbreviation or nickname for the part, then determining one of the list of candidate hypotheses having a highest matching score as a recognized answer, which is utilized to retrieve the telephone directory information from the database.

26. The program product according to claim 24, wherein a plurality of generated hypotheses are obtained in step d), and correspond to an expanded grammar utilized in the second speech recognition processing.

27. The program product according to claim 24, wherein the second speech recognition processing is performed with an expanded grammar by expanding at least one field of entries stored in the database, based on corresponding information in the at least one field of entries as obtained from the list of candidate hypotheses.

28. The program product according to claim 24, wherein the second speech recognition processing performed in step e) is performed using a grammar different than what is used by the first speech recognition processing performed in step a).

29. The program product according to claim 24, further comprising:

if there are at least two of the candidate hypotheses that exceed a predetermined match score value, or none of the candidate hypotheses exceed the predetermined match score, then requesting additional information from the speaker with regards to the person for whom the speaker desires to be provided with a telephone number; and

performing the second speech recognition processing using an expanded grammar that includes the additional information.

30. The program product according to claim 24, wherein the sequence of acoustic observations corresponds to a sequence of phonemes.

31. The program product according to claim 24, wherein the sequence of acoustic observations corresponds to a sequence of words.

32. The program product according to claim 24, wherein the substitutions generated in step d) are obtained from information stored in the database.