S. H. Chung, D. I. Moldovan, and R. F. DeMara, " Parallel Computational Model 
for Integrated Speech and Natural Language Understanding," IEEE Transactions on 
Computers, Vol. 42, No. 10, October, 1993, pp. 1171 - 1183

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