<?xml version="1.0" standalone="yes"?>
<Paper uid="H89-2039">
  <Title>ACOUSTIC MODELING OF SUBWORD UNITS FOR LARGE VOCABULARY SPEAKER INDEPENDENT SPEECH RECOGNITION</Title>
  <Section position="19" start_page="289" end_page="289" type="concl">
    <SectionTitle>
SUMMARY
</SectionTitle>
    <Paragraph position="0"> In this paper we have discussed methods of acoustic modeling of basic speech sub-word units so as to provide high word recognition accuracy. We showed that for a basic set of 47 context independent phone-like units, word accuracies on the order of 86-90% could be obtailaed on a 1000 word vocabulary, in a speaker independent mode, for a grammar with a perplexity of 60, on independent test sets. When we increased the basic set of units to include context dependent units, we were able to achieve word recognition accuracies of from 91 to 93% on the same test sets. Based on outside results and some of our own preliminary evaluations, it seems clear that we can increase word recognition accuracies by about 2-3% based on known modeling techniques. The challenge for the immediate future is to learn how to increase word recognition accuracies to the 99% range, thereby making such systems useful for simple database management tasks.</Paragraph>
  </Section>
class="xml-element"></Paper>