S. H. Chung, D. I. Moldovan, and R. F. DeMara, “Massively Parallel Speech Understanding,” in Massively Parallel Artificial Intelligence, MIT Press, 1993, J. A. Hendler and H. Kitano, Ed., ISBN: 0-262-61102-3, pp. 138 – 170.

Abstract: Presents a parallel approach for integrating speech and natural language understanding. The method emphasizes a hierarchically-structured knowledge base and memory-based parsing techniques. Processing is carried out by passing multiple markers in parallel through the knowledge base. Speech specific problems such as insertion, deletion, substitution, and word boundary detection have been analyzed and their parallel solutions are provided. Results on the SNAP-1 multiprocessor show an 80% sentence recognition rate for the Air Traffic Control (ATC) domain. Furthermore, speed-up of up to 15-fold is obtained from the parallel platform which provides response times of a few seconds per sentence for the ATC domain.

Complete Paper Available at:
http://www.cal.ucf.edu/journal/J30_chung_moldovan-IEEEComp.pdf