Method, system and recording medium for automatic speech recognition using a confidence measure driven scalable two-pass recognition strategy for large list grammars

• US 20040254790A1
• Filed: 06/13/2003
• Published: 12/16/2004
• Est. Priority Date: 06/13/2003
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Ruiz, Diego, Novak, Miroslav
• Application Number:
  US10/460,311
• Publication Number:
  US 20040254790A1
• Time in Patent Office: Days
• US Class Current: 704/240
• CPC Class Codes: G10L 15/08 Speech classification or search

Abstract

A method, a system and recording medium in which automatic speech recognition may use large list grammars and a confidence measure driven scalable two-pass recognition strategy.

Claims

1. A method of automatic speech recognition, comprising:

performing a first search of a grammar to identify a word hypothesis for an utterance;

applying a confidence measure to the word hypothesis to determine whether a second search is to be conducted; and

performing a second search of the grammar if the confidence measure indicates that a second search would be beneficial.

2. The method of claim 1, wherein said confidence measure determines whether a word hypothesis having a higher probability of matching said utterance was not identified.

3. The method of claim 1, further comprising computing information for increasing a speed of the second search.

4. The method of claim 1, wherein said first search comprises a sub-optimal search.

5. The method of claim 1, wherein the first search comprises an aggressive pruning technique.

6. The method of claim 1, wherein said first search comprises a fast search and a detailed search, and wherein said aggressive pruning technique comprises:

determining a number of candidates for said hypothesis generated during said fast search; and

selecting the top candidates for processing by said detailed search if the number of candidates exceeds a threshold.

7. The method of claim 6, wherein said confidence measure evaluates if a better hypothesis may have been pruned.

8. The method of claim 1, wherein said confidence measure evaluates a likelihood that a correct match was missed.

9. The method of claim 1, wherein performing one of said first search and said second search comprises performing a fast match process and a detailed match process.

10. The method of claim 1, wherein performing one of said first search and said second search comprises performing an iterative search.

11. The method of claim 1, wherein performing one of said first search and said second search comprises:

performing a fast match to obtain a list of possible words for extension in a search tree along with corresponding scores;

combining said list of possible words with language model scores to shorten the list of possible words; and

performing a detailed match to evaluate the shortened list of possible words and to create and insert new nodes along the search tree by selecting a time stack for a new path based upon a most likely boundary time of each new node.

12. The method of claim 11, wherein said word hypothesis comprises the path in said search tree having the best likelihood of being correct.

13. The method of claim 1, wherein said confidence measure comprises an approach based on word a posteriori probabilities from at least one word graph.

14. The method of claim 1, wherein said confidence measure assesses a possibility of a search error.

15. The method of claim 14, wherein said confidence measure assesses a possibility that a better word hypothesis may have been missed.

16. The method of claim 14, wherein said confidence measure assesses the possibility of a search error by determining an average frame likelihood of the word hypothesis.

17. The method of claim 16, wherein said confidence measure determines a normalized average frame likelihood of the hypothesis.

18. The method of claim 17, wherein said confidence measure determines a search error when said normalized average frame likelihood of the word hypothesis is lower than a predetermined threshold.

19. The method of claim 1, wherein said first search comprises a search in a forward direction, and wherein said second search comprises a search in a reverse direction.

20. The method of claim 19, wherein said second search comprises a fast match search in the reverse direction from an end of the utterance to obtain a list of candidates for a last word.

21. The method of claim 19, wherein the first search generates a first list of word candidates based on said forward search direction, and wherein said second search generates a second list of word candidates based on said reverse search direction, and wherein said second search comprises:

combining said first list of word candidates with said second list of word candidates;

determining combinations of said word candidates which are legal in accordance with said grammar; and

sorting said legal combinations according to their combined likelihoods;

determining whether one of said sorted legal combinations was processed during said first search;

adding said one of said sorted legal combinations to a new list if it is determined that said one of said sorted legal combinations was not processed during said first search; and

selecting said hypothesis from said new list and from the candidates which were processed during said first search.

22. An automatic speech recognition system comprising:

means for performing a first search of a grammar to identify a word hypothesis for an utterance;

means for applying a confidence measure to the word hypothesis to determine whether a second search is to be conducted; and

means for performing a second search of the grammar if the confidence measure indicates that a second search would be beneficial.

23. A recording medium storing a program for making a computer recognize a spoken utterance, said program comprising:

instructions for performing a first search of a grammar to identify a hypothesis for an utterance;

instructions for applying a confidence measure to the utterance to determine whether a second search is to be conducted; and

instructions for performing a second search of the grammar if the confidence measure indicates that a second search would be beneficial.

24. A method of pattern recognition, comprising:

performing a first search of a rule set to identify a sequence of features for a received signal;

applying a confidence measure to the sequence of features to determine whether it would be beneficial to conduct a second search; and

performing a second search of the rule set if the confidence measure indicates that a second search would be beneficial.