An Improved DP Match for Automatic Lexicon Generation

A number of automatic lexicon construction methods have been proposed in recent years. Such approaches employ a dynamic programming (DP) match to collect statistics concerning differences between the observed phone sequence and that which was predicted by a standard lexicon. A more expressive lexicon is then constructed based upon the collected statistics for use within a speech recognition system, which offers a more accurate phone-to-word mapping. We show that the standard DP procedure leads to the introduction of spurious matches, which reduces the quality of any subsequent processing based upon the DP provided matches. In order to remove this deficiency, an iterative DP match procedure, using individual phone confusion probabilities is outlined. It was found that the iterative DP match significantly reduced the number of equiprobable matches, to the extent that for the vast majority of utterances, only one possible DP mapping resulted, thereby improving the quality of generated statistics.