Patent ID: 9460088
Filing Date: 2016-10-04
CPC Classification: G06F,G10L

Claim Text:
1. A computer-implemented method comprising: accessing decomposed training data that results from applying rewrite grammar rules to original training data, the decomposed training data comprising (i) regular words from the original training data that have not been rewritten using the set of rewrite grammar rules, and (ii) decomposed segments that result from rewriting non-lexical entities from the original training data using the rewrite grammar rules, wherein each regular word is a lexeme in a lexicon of a natural language, and wherein each non-lexical entity (i) is a composite token that is pronounced using one or more lexemes in the lexicon of the natural language, and (ii) is not itself a lexeme in the lexicon of the natural language; generating a restriction model that (i) maps language model paths for regular words to themselves, and (ii) restricts language model paths for decomposed segments for non-lexical entities; training a n-gram language model over the decomposed training data, wherein, after the training, the n-gram language model comprises at least a first portion for recognizing regular words and a second portion for recognizing non-lexical entities; constructing a restricted language model at least by composing the restriction model with the n-gram language model; constructing a decoding network at least by composing a context dependency model with a pronunciation lexicon and with the restricted language model; and performing, by an automatic speech recognizer that uses the decoding network, speech recognition on an audio data representation of a spoken utterance that references one or more non-lexical entities.