Toward domain-independent conversational speech recognition

Abstract

We describe a multi-domain, conversational test set developed for IBM?s Superhuman speech recognition project and our 2002 benchmark system for this task. Through the use of multipass decoding, unsupervised adaptation and combination of hypotheses from systems using diverse feature sets and acoustic models, we achieve a word error rate of 32.0% on data drawn from voicemail messages, two-person conversations and multiple-person meetings.