A speech understanding system based on statistical representation of semantics

Authors:
Roberto Pieraccini;Evelyne Tzoukermann;Zakhar Gorelov;Jean-Luc Gauvain;Esther Levin;Chin-Hui Lee;Jay G. Wilpon
Affiliations:
AT&T Bell Laboratories, Murray Hill, NJ;AT&T Bell Laboratories, Murray Hill, NJ;AT&T Bell Laboratories, Murray Hill, NJ;AT&T Bell Laboratories, Murray Hill, NJ;AT&T Bell Laboratories, Murray Hill, NJ;AT&T Bell Laboratories, Murray Hill, NJ;AT&T Bell Laboratories, Murray Hill, NJ
Venue:
ICASSP'92 Proceedings of the 1992 IEEE international conference on Acoustics, speech and signal processing - Volume 1
Year:
1992

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Abstract

An understanding system, designed for both speech and text input, has been implemented based on statistical representation of task specific semantic knowledge. The core of the system is the conceptual decoder, that extracts the words and their association to the conceptual structure of the task directly from the acoustic signal. The conceptual information, that is also used to disambiguate the English sentences, i. encoded following a statistical paradigm. A template generator and an SQL translator process the sentence and produce SQL code for querying a relational database. Results of the system on the official DARPA test are given.