AUTOMATICALLY GENERATING NEW WORDS FOR LETTER-TO-SOUND CONVERSION

• US 20090240501A1
• Filed: 03/19/2008
• Published: 09/24/2009
• Est. Priority Date: 03/19/2008
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: You, Jia Li, Chen, Yi Ning, Soong, Frank Kao-ping
• Application Number:
  US12/050,947
• Publication Number:
  US 20090240501A1
• Time in Patent Office: Days
• US Class Current: 704/260
• 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

Abstract

Described is a technology by which artificial words are generated based on seed words, and then used with a letter-to-sound conversion model. To generate an artificial word, a stressed syllable of a seed word is replaced with a different syllable, such as a candidate (artificial) syllable, when the phonemic structure and/or graphonemic structure of the stressed syllable and the candidate syllable match one another. In one aspect, the artificial words are provided for use with a letter-to-sound conversion model, which may be used to generate artificial phonemes from a source of words, such as in conjunction with other models. If the phonemes provided by the various models for a selected source word are in agreement relative to one another, the selected source word and an associated artificial phoneme may be added to a training set which may then be used to retrain the letter-to-sound conversion model.

Claims

1. In a computing environment, a method comprising:

generating an artificial word set comprising at least one artificial word based on a seed word; and

using the artificial word set to provide a letter-to-sound conversion model.

2. The method of claim 1 wherein generating the artificial word set includes replacing a stressed syllable of the seed word with a different syllable.

3. The method of claim 1 wherein generating the artificial words includes evaluating a stressed syllable of the seed word against a candidate syllable, and if the evaluation indicates a sufficient match, replacing the stressed syllable of the seed word with the candidate syllable.

4. The method of claim 3 wherein evaluating the stressed syllable of the seed word against the candidate syllable comparing a phonemic structure corresponding to the seed word with a phonemic structure corresponding to the candidate syllable.

5. The method of claim 3 wherein evaluating the stressed syllable of the seed word against the candidate syllable comparing a graphonemic structure corresponding to the seed word with a graphonemic structure corresponding to the candidate syllable.

6. The method of claim 1 further comprising, generating artificial phonemes from words, and using the artificial phonemes in training at least one letter-to-sound conversion model.

7. The method of claim 6 wherein generating the artificial phonemes from the words comprises generating a plurality of phonemes corresponding to a plurality of models from a selected word, determining whether the plurality of phonemes for the selected word are in agreement with respect to an agreement threshold, and if so, including the word and an associated phoneme in a training set.

8. In a computing environment, a system comprising:

a candidate generator that generates candidate parts of speech corresponding to a seed word; and

a mechanism that evaluates the candidate parts against a similar part of the seed word, and for each candidate part in which the evaluation meets a rule, generates an artificial word based on the candidate part and another part of the seed word.

9. The system of claim 8 wherein the candidate parts of speech each correspond to a candidate syllable, and wherein the similar part of the seed word comprises a primary stressed syllable.

10. The system of claim 9 wherein the rule is met when the consonant pattern of the candidate syllable corresponds to the consonant pattern of the primary stressed syllable of the seed word, or when the consonant pattern and vowel sound of the candidate syllable corresponds to the consonant pattern and vowel sound of the primary stressed syllable of the seed word.

11. The system of claim 9 wherein the primary stressed syllable is represented in a first phonemic structure, wherein each candidate syllable is represented in a second phonemic structure, and wherein the rule is met when the first and second phonemic structures match one another.

12. The system of claim 9 wherein the primary stressed syllable is represented in a first graphonemic structure, wherein each candidate syllable is represented in a second graphonemic structure, and wherein the rule is met when the first and second graphonemic structures match one another.

13. The system of claim 8 further comprising, a set of models that generate artificial phonemes from a word, and an agreement learning mechanism coupled to the set of models to determine whether the artificial phonemes for that word achieve a threshold agreement, and if so, to add the word and an associated phoneme to a training set used in retraining the models.

14. One or more computer-readable media having computer-executable instructions, which when executed perform steps, comprising:

selecting a seed word;

comparing a stressed syllable of the seed word against a candidate syllable with respect to a replacement rule; and

when the stressed syllable of the seed word and the candidate syllable satisfy the replacement rule, generating a different word from the seed word by replacing the stressed syllable of the seed word with the candidate syllable to form the different word.

15. The one or more computer-readable media of claim 14 wherein the replacement rule comprises a phonemic structure rule, and wherein comparing the stressed syllable of the seed word against the candidate syllable comprises evaluating a phonemic structure corresponding to the stressed syllable with a phonemic structure corresponding to the candidate syllable.

16. The one or more computer-readable media of claim 14 wherein the replacement rule comprises a graphonemic structure rule, and wherein comparing the stressed syllable of the seed word against the candidate syllable comprises evaluating a graphonemic structure corresponding to the stressed syllable with a graphonemic structure corresponding to the candidate syllable.

17. The one or more computer-readable media of claim 14 having further computer-executable instructions comprising, providing the different word for use with a letter-to-sound conversion model.

18. The one or more computer-readable media of claim 17 having further computer-executable instructions comprising, using the letter-to-sound conversion model to generating artificial phonemes from a source of words.

19. The one or more computer-readable media of claim 18 wherein generating the artificial phonemes from the source of words comprises generating a plurality of phonemes from a selected source word, determining whether the plurality of phonemes for the selected source word are in agreement relative to one another with respect to an agreement threshold, and if so, including the selected source word and an associated artificial phoneme for that selected source word in a training set.

20. The one or more computer-readable media of claim 19 having further computer-executable instructions comprising, using the training set to retrain the letter-to-sound conversion model.