Method for Constructing Pronunciation Dictionaries

• US 20110238412A1
• Filed: 03/26/2010
• Published: 09/29/2011
• Est. Priority Date: 03/26/2010
• Status: Abandoned Application

• Current Assignee: Mitsubishi Electric Research Laboratories, Inc. (Mitsubishi Electric Corporation)
• Original Assignee: Mitsubishi Electric Research Laboratories, Inc. (Mitsubishi Electric Corporation)
• Inventors: Ezzat, Antoine
• Application Number:
  US12/732,231
• Publication Number:
  US 20110238412A1
• Time in Patent Office: Days
• US Class Current: 704/10
• CPC Class Codes: G10L 15/187 Phonemic context, e.g. pronunciation rules, phonotactical constraints or phoneme n-grams

Abstract

Embodiments of the invention disclose a system and a method for constructing a pronunciation dictionary by transforming an unaligned entry to an aligned entry. The unaligned entry and the aligned entry include a set of words and a set of pronunciations corresponding to the set of words. The method aligns each word in the aligned entry with a subset of pronunciations by determining a pronunciation prediction for each word, such that there is one-to-one correspondence between the word and the pronunciation prediction; mapping each pronunciation prediction to the subset of pronunciations to produce a predictions-pronunciation map having each pronunciation prediction aligned with the subset of pronunciations; and determining the aligned entry based on the predictions-pronunciation map using the one-to-one correspondence between the word and the pronunciation prediction.

Claims

1. A method for constructing a pronunciation dictionary by transforming an unaligned entry to an aligned entry, wherein the unaligned entry and the aligned entry include a set of words and a set of pronunciations corresponding to the set of words, and wherein each word in the aligned entry is aligned with a subset of pronunciations from the set of pronunciations, comprising the steps of:

determining, for each word in the set of words, a pronunciation prediction, such that there is one-to-one correspondence between the word and the pronunciation prediction;

mapping each pronunciation prediction to the subset of pronunciations to produce a predictions-pronunciation map having each pronunciation prediction aligned with the subset of pronunciations; and

determining the aligned entry based on the predictions-pronunciation map using the one-to-one correspondence between the word and the pronunciation prediction, wherein the steps of the method are performed by a processor.

2. The method of claim 1, wherein the pronunciations and predictions are represented as a concatenation of syllables, further comprising:

concatenating the syllables of the predictions in the set of predictions forming an A-string, wherein the syllables of a pronunciation form an A-chunk;

concatenating syllables of the pronunciation predictions forming a B-string, wherein the syllables of the pronunciation prediction form a B-chunk;

determining an alignment path between letters in the A-string and letters in the B-string;

determining an A-chunk-to-B-chunk map based on the alignment path; and

determining the predictions-pronunciation map based on the A-chunk-to-B-chunk map.

3. The method of claim 2, wherein the A-chunk-to-B-chunk map is a one-to-one chunk map.

4. The method of claim 2, wherein the A-chunk-to-B-chunk map is a one-to-many chunk map, further comprising:

resolving the A-chunk-to-B-chunk map into a one-to-one chunk map.

5. The method of claim 4, wherein the resolving further comprising:

determining a Cartesian product of one-to-one chunk maps of A-chunks to B-chunks mapping allowed by the one-to-many chunk map;

calculating a cumulative edit distance of each one-to-one chunk map; and

selecting the one-to-one chunk map with a lowest cumulative edit distance.

6. The method of claim 5, further comprising

determining an edit distance for each mapping in each one-to-one chunk map to produce edit distances of each one-to-one chunk map;

and

determining the cumulative edit distance by summing up the edit distances of each one-to-one chunk map.

7. The method of claim 1, further comprising:

selecting the pronunciation prediction from an internal dictionary.

8. The method of claim 1, further comprising:

determining the pronunciation prediction using a grapheme-to-phoneme converter.

9. The method of claim 1, further comprising:

selecting an orthographic form of the word as the pronunciation prediction of that word.

10. The method of claim 2, further comprising:

determining an a cost matrix representing costs of insertion, deletion, and substitution between the between the letters in the A-string and the letters in the B-string;

determining and an index matrix representing indices of the elements minimizing the costs; and

determining the alignment path based on the index matrix.

11. The method of claim 10, wherein the alignment path is a path starting from a bottom-right-most element in the index matrix and retraced backwards by following the indices of the elements minimizing the costs.

12. The method of claim 11, wherein the element in the index matrix represents the cost of the deletion, further comprising:

placing two asterisks side-by-side horizontally on the alignment path.

13. The method of claim 11, wherein the element in the index matrix represents the cost of the insertion, further comprising:

placing two asterisks side-by-side vertically on the alignment path.

14. The method of claim 11, wherein the element in the index matrix represents the cost of the substitution, further comprising:

placing two asterisks side-by-side diagonally on the alignment path.

15. The method of claim 1, wherein the aligned entry includes a set of word-pronunciation mappings, further comprising:

removing a word-pronunciation mapping having a probability below a threshold.

16. The method of claim 15, further comprising

determining, for each word in the set of words, a frequency count c(w, p), wherein the frequency count indicates a number of mappings between a word w and a pronunciation p;

determining the probability P(w, p) of the word-pronunciation mapping between the word w and the pronunciation p based on the frequency count c(w, p) and frequency counts of the word with pronunciations q according to

17. A method for constructing a pronunciation dictionary from a set of unaligned entries, wherein an unaligned entry includes a set of words and a set of pronunciations corresponding to the set of words, comprising the steps of:

transforming iteratively each unaligned entry into an aligned entry, wherein each word in the aligned entry is aligned with a subset of pronunciations from the set of pronunciations;

storing each aligned entry in an internal dictionary; and

outputting the internal dictionary as the pronunciation dictionary, wherein the steps of the method are performed by a processor.

18. The method of claim 17, wherein the transforming further comprising:

determining for each word in the set of words a pronunciation prediction, such that there is one-to-one correspondence between the word and the pronunciation prediction;

mapping each pronunciation prediction to the subset of pronunciations to produce a predictions-pronunciation map having each pronunciation prediction aligned with the subset of pronunciations; and

determining the aligned entry based on the predictions-prons map using the one-to-one correspondence between the word and the pronunciation prediction.

19. The method of claim 17, wherein the aligned entry includes a set of word-pronunciation mappings, further comprising:

removing a word-pronunciation mapping having a probability below a threshold.

20. A system for constructing a pronunciation dictionary by transforming an unaligned entry to an aligned entry, wherein the unaligned entry and the aligned entry include a set of words and a set of pronunciations corresponding to the set of words, and wherein each word in the aligned entry is aligned with a subset of pronunciations from the set of pronunciations, comprising:

pronunciation prediction sub-module for determining, for each word in the set of words, a pronunciation prediction, such that there is one-to-one correspondence between the word and the pronunciation prediction;

dynamic programming sub-module for mapping each pronunciation prediction to the subset of pronunciations to produce a predictions-pronunciation map having each pronunciation prediction aligned with the subset of pronunciations; and

a processor configured for determining the aligned entry based on the predictions-pronunciation map using the one-to-one correspondence between the word and the pronunciation prediction.