초록
영어
The example‐based machine translation system in the specific domain can be developed in a short time with a high translation quality. Though an EBMT system can be transplanted to a new
domain quickly, when faces to the need for the multi‐doamins translation, its advantage in domain
adaptability will be affected. In order to solve this problem a new domain sensative EBMT translation model is proposed. Through combining the text‐classsify technique, the proposed EBMT will judge the input text and then select the most appropriate example base for the following translations. The experiments showed that this method can improve the performance of the EBMT system and meet the need for Olympicsoriented multi‐domains translations in some
extents
목차
Abstract
1. Introduction
2. Classfication based domain adaptation forEBMT
2.1. What is EBMT
2.2. Auto Word Alignment Based EBMT
2.3. Text‐classify based EBMT domain selfadaptingframework
3. Experiments and Discussion
4. Conclusion
References
1. Introduction
2. Classfication based domain adaptation forEBMT
2.1. What is EBMT
2.2. Auto Word Alignment Based EBMT
2.3. Text‐classify based EBMT domain selfadaptingframework
3. Experiments and Discussion
4. Conclusion
References
저자정보
참고문헌
자료제공 : 네이버학술정보