Toward High Performance Machine Translation: Preliminary Results from Massively Parallel Memory-Based Translation on SNAP

Hiroaki Kitano, Dan Moldovan, Seungho Cha


Abstract
This paper describes a memory-based machine translation system developed for the Semantic Net- work Array Processor (SNAP). The goal of our work is to develop a scalable and high-performance memory-based machine translation system which utilizes the high degree of parallelism provided by the SNAP machine. We have implemented an experimental machine translation system DMSNAP as a central part of a real-time speech-to-speech dia- logue translation system. It is a SNAP version of the ΦDMDIALOG 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.
Anthology ID:
1991.mtsummit-papers.15
Volume:
Proceedings of Machine Translation Summit III: Papers
Month:
July 1-4
Year:
1991
Address:
Washington DC, USA
Venue:
MTSummit
SIG:
Publisher:
Note:
Pages:
93–100
Language:
URL:
https://aclanthology.org/1991.mtsummit-papers.15
DOI:
Bibkey:
Cite (ACL):
Hiroaki Kitano, Dan Moldovan, and Seungho Cha. 1991. Toward High Performance Machine Translation: Preliminary Results from Massively Parallel Memory-Based Translation on SNAP. In Proceedings of Machine Translation Summit III: Papers, pages 93–100, Washington DC, USA.
Cite (Informal):
Toward High Performance Machine Translation: Preliminary Results from Massively Parallel Memory-Based Translation on SNAP (Kitano et al., MTSummit 1991)
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PDF:
https://aclanthology.org/1991.mtsummit-papers.15.pdf