High performance natural language processing on semantic network array processor

Authors:
Hiroaki Kitano;Dan Moldovan;Seungho Cha
Affiliations:
Center for Machine Translation, Carnegie Mellon University, Pittsburgh, PA;Parallel Knowledge Processing Laboratory, Department of Electrical Engineering-Systems, University of Southern California, Los Angeles, CA;Parallel Knowledge Processing Laboratory, Department of Electrical Engineering-Systems, University of Southern California, Los Angeles, CA
Venue:
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 2
Year:
1991

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Abstract

This paper describes a natural language processing system developed for the Semantic Network Array Processor (SNAP). The goal of our work is to develop a scalable and high-performance natural language processing system which utilizes the high degree of parallelism provided by the SNAP machine. We have implemented an experimental machine translation system as a central part of a real-time speech-to-speech dialogue translation system. It is a SNAP version of the Φ DMDIAIOG speech-to-speech translation system. Memory-based natural language processing and syntactic constraint network model has been incorporated using parallel marker-passing which is directly supported from hardware level. Experimental results demonstrate that the parsing of a sentence is done in the order of milliseconds.