The goal in speech-message information retrieval is to categorize an inputspeech
utterance according to a predefined notion ofa topic, or message class. The
components of a speech-message information-retrieval system include an acoustic
front end that provides an incomplete transcription of a spoken message, and a
message classifier that interprets the incomplete transcription and classifies the
message according to message category. The techniques and experiments described
in this paper concern the integration ofthese components, and represent the first
demonstration of a complete system that accepts speech messages as input and
produces an estimated message class as output. The promising results obtained in
information retrieval on conversational speech messages demonstrate the feasibility
ofthe technology.