Speech recognition based on pronunciation modeling
View Patent ↗A system and method for performing speech recognition is disclosed. The method comprises receiving an utterance, applying the utterance to a recognizer with a language model having pronunciation probabilities associated with unique word identifiers for words given their pronunciations and presenting a recognition result for the utterance. Recognition improvement is found by moving a pronunciation model from a dictionary to the language model.
1. A method comprising:
approximating transcribed speech, via a processor, using a phonemic transcription dataset associated with a speaker, to yield a language model, where the phonemic transcription dataset is based on a pronunciation model of the speaker;
incorporating, into the language model, pronunciation probabilities associated with respective unique labels for each different pronunciation of a word, wherein the respective unique label for a most frequent word indicates a special status in the language model; and
after incorporating the pronunciation probabilities into the language model, recognizing an utterance using the language model.
2. The method of claim 1 , further comprising:
removing the pronunciation probabilities from a pronunciation dictionary.
3. The method of claim 1 , wherein the language model is generated by modeling pronunciation dependencies across word boundaries.
4. The method of claim 1 , wherein one of contextual dependencies and consistency in pronunciation style exist throughout the utterance.
5. The method of claim 1 , wherein the pronunciation probabilities in the language model further comprise pronunciation dependent word pairs as lexical items that change a behavior of the language model to approximate higher order n-gram language models.
6. The method of claim 1 , further comprising:
creating a wide context pronunciation model based on having the pronunciation probabilities in the language model; and
determining a probability of observing a particular word in the utterance using the wide context pronunciation model.
7. The method of claim 1 , wherein the pronunciation probabilities comprise a set of most frequent words each with more than one pronunciation alternative.
8. The method of claim 7 , wherein the more than one pronunciation alternative is in the language model.
9. A system comprising:
a processor; and
a computer-readable storage medium having instructions stored which, when executed on the processor, cause the processor to perform operations comprising:
approximating transcribed speech using a phonemic transcription dataset associated with a speaker, to yield a language model, where the phonemic transcription dataset is based on a pronunciation model of the speaker;
incorporating, into the language model, pronunciation probabilities associated with respective unique labels for each different pronunciation of a word, wherein the respective unique label for a most frequent word indicates a special status in the language model; and
after incorporating the pronunciation probabilities into the language model, recognizing an utterance using the language model.
10. The system of claim 9 , wherein the computer-readable storage medium has additional instructions stored which result in the operations further comprising:
removing the pronunciation probabilities from a pronunciation dictionary.
11. The system of claim 9 , wherein the language model is generated by modeling pronunciation dependencies across word boundaries.
12. The system of claim 9 , wherein one of contextual dependencies and consistency in pronunciation style exist throughout the utterance.
13. The system of claim 9 , wherein the pronunciation probabilities in the language model further comprise pronunciation dependent word pairs as lexical items that change a behavior of the language model to approximate higher order n-gram language models.
14. The system of claim 9 , the computer-readable storage medium having additional instructions stored which result in the operations further comprising:
creating a wide context pronunciation model based on having the pronunciation probabilities in the language model; and
determining a probability of observing a particular word in the utterance using the wide context pronunciation model.
15. The system of claim 9 , wherein the pronunciation probabilities comprise a set of most frequent words each with more than one pronunciation alternative.
16. The system of claim 15 , wherein the more than one pronunciation alternative is in the language model.
17. A computer-readable storage device having instructions stored which, when executed on a processor, cause the processor to perform operations comprising:
approximating transcribed speech using a phonemic transcription dataset associated with a speaker, to yield a language model, where the phonemic transcription dataset is based on a pronunciation model of the speaker;
incorporating, into the language model, pronunciation probabilities associated with respective unique labels for each different pronunciation of a word, wherein the respective unique label for a most frequent word indicates a special status in the language model; and
after incorporating the pronunciation probabilities into the language model, recognizing an utterance using the language model.
18. The computer-readable storage device of claim 17 , the computer-readable storage device having additional instructions stored which result in the operations further comprising:
removing the pronunciation probabilities from a pronunciation dictionary.
19. The computer-readable storage device of claim 17 , wherein the language model is generated by modeling pronunciation dependencies across word boundaries.
20. The computer-readable storage device of claim 17 , wherein one of contextual dependencies and consistency in pronunciation style exist throughout the utterance.