Patent ID: 7395205

Claim:
In an Automatic Speech Recognition (ASR) system having at least two language models, a method for combining language model scores generated by at least two language models, said method comprising the steps of: generating a list of most likely words for a current word in a word sequence uttered by a speaker, and acoustic scores corresponding to the most likely words; computing language model scores for each of the most likely words in the list, for each of the at least two language models; respectively and dynamically determining a set of coefficients to be used to combine the language model scores of each of the most likely words in the list, based on a context of the current word; and respectively combining the language model scores of each of the most likely words in the list to obtain a composite score for each of the most likely words in the list, using the set of coefficients determined therefor; wherein said determining step comprises the steps of: dividing text data for training a plurality of sets of coefficients into partitions, depending on word counts corresponding to each of the at least two language models; and for each of the most likely words in the list, dynamically selecting the set of coefficients from among the plurality of sets of coefficients so as to maximize the likelihood of the text data with respect to the at least two language models.