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Our goal is to better understand how integration of prosodic information, speech recognition and parsing can impact the problem of information extraction from spoken documents. There are four key themes to our proposed research:

  • utilizing parsing in information retrieval,
  • integrating prosodic information in parsing spoken language,
  • incorporating uncertainty in parsing to handle speech recognition errors,
  • improvements to speech recognition of spontaneous speech.

This research will provide initial steps towards information extraction from spoken documents or from any text (such as encyclopedias), and can serve as the basis for a sorely needed sophisticated web browser technology and data mining applications. The ability to handle and annotate informal speech and text is critical for systems that will enable people who currently under-utilize computers to become full participants in the information revolution.
Brown Laboratory for Linguistic and Information Processing Signal, Speech, and Language Interpretation Laboratory at the University of Washington Center for Language and Speech Processing at Johns Hopkins University Institute for Signal and Information Processing, Mississippi State University
This material is based upon work supported by the National Science Foundation under Grant No. IIS0095940. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.