Automatic alternative transcription generation and vocabulary selection for flexible word recognizers

In accordance with the new emerging voice response systems that use flexible vocabulary recognizers (FVRs), the prediction of word confusabilities have received increasing interest during the last few years. We present a new method for transcription confusabilities estimation based on a new statistical modelling criterion. We propose the use of the new transcription confusability measure in two different word error rate (WER) reduction procedures for FVRs: an automatic vocabulary selection procedure suitable for those applications where the set of vocabulary words is not totally defined by the application, and an automatic procedure for generation of alternative transcriptions. Experimental results using a telephonic database show a 20% WER relative reduction using the automatic alternative transcription generation procedure for a 37 word vocabulary, and over a 50% (20%) WER relative reduction using our unrestricted (restricted by groups of synonyms) vocabulary selection procedure instead of random word selection