Generating large units of graphonemes with mutual information criterion for letter to sound conversion
First Claim
1. A method of segmenting words into component parts, the method comprising:
- a processor determining a mutual information score for a pair of graphoneme units, comprising a first graphoneme unit and a second graphoneme unit, using the probability of the first graphoneme unit appearing immediately after the second graphoneme unit, the unigram probability of the first graphoneme unit and the unigram probability of the second graphoneme unit, each graphoneme unit comprising at least one letter in the spelling of a word;
a processor using the mutual information score to combine the first and second graphoneme units into a larger graphoneme unit; and
in a dictionary comprising segmentations of words into sequences of graphoneme units, a processor replacing the first and second graphoneme units with the larger graphoneme unit in each sequence of graphoneme units in which the first graphoneme unit appears immediately after the second graphoneme unit.
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Accused Products
Abstract
A method and apparatus are provided for segmenting words into component parts. Under the invention, mutual information scores for pairs of graphoneme units found in a set of words are determined. Each graphoneme unit includes at least one letter. The graphoneme units of one pair of graphoneme units are combined based on the mutual information score. This forms a new graphoneme unit. Under one aspect of the invention, a syllable n-gram model is trained based on words that have been segmented into syllables using mutual information. The syllable n-gram model is used to segment a phonetic representation of a new word into syllables. Similarly, an inventory of morphemes is formed using mutual information and a morpheme n-gram is trained that can be used to segment a new word into a sequence of morphemes.
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Citations
17 Claims
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1. A method of segmenting words into component parts, the method comprising:
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a processor determining a mutual information score for a pair of graphoneme units, comprising a first graphoneme unit and a second graphoneme unit, using the probability of the first graphoneme unit appearing immediately after the second graphoneme unit, the unigram probability of the first graphoneme unit and the unigram probability of the second graphoneme unit, each graphoneme unit comprising at least one letter in the spelling of a word; a processor using the mutual information score to combine the first and second graphoneme units into a larger graphoneme unit; and in a dictionary comprising segmentations of words into sequences of graphoneme units, a processor replacing the first and second graphoneme units with the larger graphoneme unit in each sequence of graphoneme units in which the first graphoneme unit appears immediately after the second graphoneme unit. - View Dependent Claims (2, 3, 4, 5, 6)
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7. A computer-readable storage medium having computer-executable instructions stored thereon that when executed by a processor cause the processor to perform steps comprising:
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determining mutual information scores for pairs of graphoneme units found in a set of words, each graphoneme unit comprising at least one letter and each mutual information score for a pair of graphoneme units based on the probability of one graphoneme unit of the pair of graphoneme units appearing immediately after the other graphoneme unit of the pair of graphoneme units, and the unigram probabilities of each graphoneme unit in the pair of graphoneme units; combining the graphoneme units of one pair of graphoneme units to form a new graphoneme unit based on the mutual information scores; and updating a segmentation of a word comprising a set of graphoneme units for the word that includes the pair of graphoneme units by replacing the pair of graphoneme units in the segmentation with the new graphoneme unit. - View Dependent Claims (8, 9, 10, 11, 12, 13, 14, 15)
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16. A method of segmenting a word into syllables, the method comprising:
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a processor segmenting a set of words into phonetic syllables using mutual information scores wherein using a mutual information score comprises computing a mutual information score for two phones by dividing the probability of two phones appearing next to each other in the set of words by the unigram probabilities of each of the two phones appearing in the set of words; a processor using the segmented set of words to train a syllable n-gram model; and a processor using the syllable n-gram model to segment a phonetic representation of a word into syllables via forced alignment.
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17. A method of segmenting a word into morphemes, the method comprising:
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a processor segmenting a set of words into morphemes using mutual information scores wherein using mutual information scores comprises computing a mutual information score for two letters based on the probability of the two letters appearing next to each other in the set of words and the unigram probabilities of each of the two letters appearing in the set of words; a processor using the segmented set of words to train a morpheme n-gram model; and a processor using the morpheme n-gram model to segment a word into morphemes via forced alignment.
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Specification