Hardware for hidden Markov-model-based, large-vocabulary real-time speech recognition

Abstract

SRI and U.C. Berkeley have begun a cooperative effort to develop a new architecture for real-time implementation of spoken language systems (SLS). Our goal is to develop fast speech recognition algorithms, and supporting hardware capable of recognizing continuous speech from a bigram-or trigram-based 20,000-word vocabulary or a 1,000-to 5,000word SLS.