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<Paper uid="H90-1018">
  <Title>Hardware for Hidden Markov-Model-Based, Large-Vocabulary Real-Time Speech Recognition</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> 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.</Paragraph>
  </Section>
class="xml-element"></Paper>