Selection of superwords based on criteria relevant to both speech recognition and understanding

• US 6,044,337 A
• Filed: 10/29/1997
• Issued: 03/28/2000
• Est. Priority Date: 10/29/1997
• Status: Expired due to Term

• Current Assignee: Nuance Communications, Inc. (Microsoft Corporation)
• Original Assignee: AT&T Corporation (AT&T, Inc.)
• Inventors: Gorin, Allen Louis, Riccardi, Giuseppe, Wright, Jeremy Huntley
• Primary Examiner(s): Isen, Forester W
• Assistant Examiner(s): EDOUARD, PATRICK NESTOR
• Application Number:
  US08/960,289
• Time in Patent Office: 881 Days
• Field of Search: 704/1, 704/9, 704/10, 704/251, 704/255, 704/256, 704/257
• US Class Current: 704/1
• CPC Class Codes: G10L 15/18 using natural language modelling
• CPC Class Codes: G10L 15/197 Probabilistic grammars, e.g. word n-grams

Abstract

This invention is directed to the selection of superwords based on a criterion relevant to speech recognition and understanding. Superwords are used to refer to those word combinations which are so often spoken that are recognized or should have models for such combinations reflected in its grammar. The selected superwords are placed in a lexicon is then used by a speech recognizer to improve recognition of input speech utterances for the proper routing of a user'"'"'s task objectives.

Claims

1. A method for determining superwords and meaningful phases, comprising the steps of:

determining superwords from a set of generated candidate phrases contained in a database of observed sequences of words, symbols and/or sounds, the database having a perplexity value based on a language model;

determining meaningful phrases based on commonality measurements; and

incorporating the determined meaningful phrases from the database into the language model.

2. The method of claim 1, wherein the step of determining superwords determines how each candidate phrase affects the perplexity value of the database so that if the perplexity value decreases, the candidate phrase is added to the database as a superword, and if the perplexity value is not decreased, the candidate phrase is not added to the database.

3. The method of claim 1, wherein the step of determining the meaningful phrases determines meaningful phrases based on salience and mutual information measurements.

4. The method of claim 1, further comprising the step of:

training a speech recognizer using the database.

5. The method of claim 1, further comprising the step of:

interpreting a user'"'"'s input using the database.

6. The method of claim 5, further comprising the step of:

implementing one or more of a set of task objectives based on the user'"'"'s input.

7. An apparatus that determines superwords and meaningful phases, comprising:

a database of observed sequences of words, symbols and/or sounds containing a generated set of candidate phrases, the database having a perplexity value based on a language model;

superword selecting means for selecting superwords, the selected superwords being incorporated from the database into the language model; and

meaningful phrase selecting means for selecting meaningful phrases based on commonality measurements, the selected meaningful phrases being incorporated from the database into the language model.

8. The apparatus of claim 7, wherein the superword selecting means creates a ranked set of candidate phrases from the database.

9. The apparatus of claim 8, wherein the superword selecting means inputs each of the candidate phrases into the database and determines whether the inserted candidate phrase decreases the perplexity value of the database.

10. The apparatus of claim 9, wherein the superword selecting means determines that if the perplexity value decreases, the inserted candidate phrase is added to the database as a superword, and if the perplexity is not decreased, the inserted candidate phrase is not added to the database.

11. The apparatus of claim 7, wherein the meaningful phrase selecting means selects the meaningful phrases based on salience and mutual information measurements.

12. The apparatus of claim 7, further comprising:

recognizing means for recognizing, based on a user'"'"'s input, at least one meaningful phrase or superword contained in the database.

13. The apparatus of claim 12, wherein the database trains the recognizing means.

14. The apparatus of claim 12, further comprising:

interpretation means for making a classification decision based on the recognized meaningful phrases and superwords.

15. The apparatus of claim 14, wherein the interpretation means implements one or more task objectives based on the user'"'"'s input.

16. The apparatus of claim 15, further comprising:

dialog means for obtaining additional input from the user in order to implement one or more of the task objectives.

17. An apparatus that determines superwords and meaningful phases, comprising:

a database of observed sequences of words, symbols and/or sounds containing a generated set of candidate phrases, the database having a perplexity value based on a language model;

a superword selector that selects superwords, the superword selector incorporating the selected superwords from the database into the language model; and

a meaningful phrase selector that selects meaningful phrases based on commonality measurements, the meaningful phrase selector incorporating the selected meaningful phrases from the database into the language model.

18. The apparatus of claim 17, wherein the superword selector creates a ranked set of candidate phrases from the database.

19. The apparatus of claim 18, wherein the superword selector inserts each separate candidate phrase into the database and determines whether the inserted candidate phrase decreases the perplexity value of the database.

20. The apparatus of claim 19, wherein the superword selector determines that if the perplexity value decreases, the candidate phrase is added to the database as a superword, and if the perplexity is not decreased, the candidate phrase is not added to the database.

21. The apparatus of claim 17, wherein the meaningful phrase selector selects a set of meaningful phrases based on salience and mutual information measurements.

22. The apparatus of claim 17, further comprising:

a recognizer that recognizes, from a user'"'"'s input, at least one of the selected meaningful phrases and superwords contained in the database.

23. The apparatus of claim 22, wherein the database trains the recognizer.

24. The apparatus of claim 22, further comprising:

an interpretation module that makes a classification decision based on the recognized meaningful phrases and superwords.

25. The apparatus of claim 24, wherein the interpretation module implements one or more task objectives based on the user'"'"'s input.

26. The apparatus of claim 25, further comprising:

a dialog manager that obtains additional input from the user to implement one or more of the task objectives.