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<Paper uid="H91-1088">
  <Title>PROGRESS REPORT FOR DARPA SLS PROGRAM</Title>
  <Section position="3" start_page="0" end_page="0" type="metho">
    <SectionTitle>
REVIEW OF CURRENT WORK
</SectionTitle>
    <Paragraph position="0"> Dragon Systems has continued to develop its continuous speech recognition capability on personal computers, with a strong focus on achieving real-time or near real-time performance in that environment We are now able to run recognition using vocabularies of up to 5000 words, although the larger vocabularies do slow down the recognition substantially; therefore more work still needs to be done to improve the computational efficiency of our algorithms.</Paragraph>
    <Paragraph position="1"> The recogn~er now has an interface which allows for on-line adaptation. This interface constitutes a beginning step in the development of a &amp;quot;DragonDictate&amp;quot;-like er~ correction facility fet continuous speech, one that would allow a user to dictate text, correcting en~s as he proceeds, with the system gradually improving its models by using the feedback from the user's error corrections.</Paragraph>
    <Paragraph position="2"> In recent months Dragon has turned its attention to Resource Management, and this has resulted in a new focus on the special characteristics of this particular task; of course, Dragon continues to place a slrong emphasis on improving overall recognition accuracy in a way that will benefit the general run of speech recognition appfications. In order to use the digitized speech supplied on CD-Rom the first step was to write software that would closely emulate the old signal processing done on our standard hardware, so that we would have a baseline perf~rnance assessment that could be used to evaluate the new, more computationally demanding signal processing algorithms that we plan to implement in the near future. We then went through several cycles of development on our adaptation and Iraining alg~-ithms in the course of gradually improving our perfefmance on the RM1 development test data and are still in a period of rapid development. To enhance our ability to perform experiments with the large quantity of speech data that has been supplied, we ported our recognizer to the IBM RS-6000 workstation. We have a collection of these machines and, now that they have been networked together, it is possible to do experiments on many speakers simulmeously. The recognizer has also been ported to the Apple Macintosh computer.</Paragraph>
    <Paragraph position="3"> With our focus on improving the accuracy of the recognizer has come a concern with the sources of error. To enhance our ability to study our sources of error, we have developed a diagnostic program known as ERRSPEC, which displays segmented spectrograms of utterances and models, together with a variety of revealing plots that highlight where the recognition algorithm has gone wrong.</Paragraph>
  </Section>
  <Section position="4" start_page="0" end_page="414" type="metho">
    <SectionTitle>
FUTURE PLANS
</SectionTitle>
    <Paragraph position="0"> Dragon plans to continue its work on the Resource Management Task and to begin work on ATIS in the coming months. A primary goal will continue to be improvements in our overall accuracy, but with the additional aim of moving to a mcfe broadly based speaker independent mode~g strategy, one that is likely to be based on mixture distributions (at the PEL level, at the PIC level, and at the word level). Investigation of alternative signal processing algorithms will also be a high priority, as we move away from the computational constraints that our old hardware had placed on us. Post processing slrategies based on the outputs from the N-Best algorithm will also be explored.</Paragraph>
  </Section>
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