System and method to improve performance of a speech recognition system by measuring amount of confusion between words

A method for improving the performance of an automatic speech recognition (ASR) system that uses a language model based on a corpus data set which includes words from a generic corpus data set and words from a domain-specific data set, using a confusion index indicative of the amount of confusion between words from the generic corpus data set and the domain-specific data set, comprising:

• determining the confusion index using a method comprising:
• receiving a first word from the domain-specific data set and a second word from the generic corpus data set;
• calculating an acoustic score indicative of the acoustic distance between the first word and the second word using a lexicon having a phonetic breakdown of the first word and the second word;
• calculating a weighted language score indicative of the likelihood of the first word and the second word occurring in the corpus data set;
• wherein the weighted language score comprises an equation:
• W(U1+U2), where U1 and U2 are unigram values of the first word and the second word, respectively, and W is a weighting;
• and
• calculating the confusion index (CI) using the acoustic score and the weighted language score.

A method for improving the performance of an automatic speech recognition (ASR) system that uses a language model based on a corpus data set which includes words from a corpus first data set and a domain-specific second data set, using an amount of confusion between words, comprising:

• calculating a confusion index (CI), comprising:
• receiving a first word from the first data set and a second word from the second data set;
• calculating an acoustic score indicative of the acoustic distance between the first word and the second word using a lexicon having a phonetic breakdown of the first word and the second word;
• calculating a weighted language score indicative of the likelihood of the first word and the second word occurring in the corpus data set;
• wherein the weighted language score comprises an equation:
• W(U1+U2), where U1 and U2 are unigram values of the first word and the second word, respectively, and W is a weighting factor;
• and
• calculating the confusion index (CI) using the acoustic score and the weighted language score.