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<Paper uid="H94-1065">
  <Title>ADAPTATION TO NEW MICROPHONES USING TIED-MIXTURE NORMALIZATION</Title>
  <Section position="2" start_page="0" end_page="0" type="intro">
    <SectionTitle>
ABSTRACT
BBN Systems and Technologies
</SectionTitle>
    <Paragraph position="0"> In this paper, we present several approaches designed to increase the robustness of BYBLOS, the BBN continuous speech recognition system. We address the problem of increased degradation in * performance when there is mismatch in the characteristics of the training and the test microphones. We introduce a new supervised adaptafi.~n algor/thm that computes a transformation from the trainhag microphone codebook to that of a new microphone, given some information about the new microphone. Results are reported for the development and evaluation test sets of the 1993 ARPA CSR Spoke 6 WSJ task, which consist of speech recorded with two al- * temate microphones, a stand-mount and a telephone microphone.</Paragraph>
    <Paragraph position="1"> The proposed algorithm improves the performance of the system * * when tested with the stand-mount microphone by reducing the difference ha error rate between the high quality training microphone and the alternate stand-mount microphone recordings by a factor of 2. Several results are presented for the telephone speech leading * to important conclusions: a) the performance on telephone speech is dramaticaUy improved by simply retraining the system on the high-quality training data after they have been bandlimited in the telephone bandwith; and b) additional training data recorded with the high quality microphone give luther substantial improvement ha performance.</Paragraph>
  </Section>
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