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

Abstract

Systems and methods to improve the performance of an automatic speech recognition (ASR) system using a confusion index indicative of the amount of confusion between words are described, where a confusion index (CI) or score is calculated by receiving a first word (Word1) and a second word (Word2), calculating an acoustic score (A12) indicative of the phonetic difference between Word1 and Word2, calculating a weighted language score (W(U1+U2), indicative of a weighted likelihood (or word frequency) of Word1 and Word2 occurring in the corpus, the confusion index CI incorporating both the acoustic score and the weighted language score, such that the CI for words that sound alike and have a high likelihood of occurring in the corpus will be higher than the CI for words that sound alike and do not have a high likelihood of occurring in the corpus. In some embodiments, the CI may be used to artificially boost uncommon words in a corpus to improve their visibility, to add context to uncommon words in a corpus to avoid conflict with common words, and to remove unimportant words from the lexicon to avoid conflicts with other corpus words.