Example-Based Translation on Massivcly Parallel Computers
| Project/Area Number |
05680292
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| Research Category |
Grant-in-Aid for General Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Research Field |
Intelligent informatics
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| Research Institution | Japan Advanced Institute of Science and Technology, Hokuriku |
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Principal Investigator |
SATO Satoshi JAIST,School of Information Science, Associate Professor., 情報科学研究科, 助教授 (30205918)
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| Project Period (FY) |
1993 – 1994
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| Project Status |
Completed (Fiscal Year 1994)
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| Budget Amount *help |
¥2,000,000 (Direct Cost: ¥2,000,000)
Fiscal Year 1994: ¥1,000,000 (Direct Cost: ¥1,000,000)
Fiscal Year 1993: ¥1,000,000 (Direct Cost: ¥1,000,000)
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| Keywords | Example-Based Translation / Massively Parallel Computer / Machine Translation / Technical Terms / 論文表題 |
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| Research Abstract |
The Major results of this research are as follows.
1. We collected technical terms of Computer Science in Japanese and in English, and constructed translate database with 7,000 bilingual technical terms (translation examples).
2. We investigated the best match retrival method using Dynamic Programming. This method retrieves several translation examples similar to the retrieval input.
3. We investigated the parallel best match retriecval mcthod and implemented it on a massively parallel computer, nCUBE2.
4. We constructed a translation system of technical terms on an nCUBE2 using the parallel best match retrieval program. This system is the first machine translation system on a commercial massively parallel computer. This system shows high performance and good scalability : the performance is proportional to the number of processors, and it can be scaled up to the system with some million translation examples.
5. We constructed another translation system on a massively parallel computer, CM-5. It also shows high performance and good scalability : It is about fifteen times faster than the sequential system on a SS2.
From this research, we concluded that parallel Example-Based Translation is promising : it shows high performance and good scalability.
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Report
(3 results)
Research Products
(18 results)
