Analysis of Probability Model for Example Based Machine Translation
Keywords:
EBMT, Probability,AlgorithmAbstract
Until now, Example-based machine translation (EBMT) systems rely on heuristics to retrieve translation samples. This heuristic of takes time to fix and can make’s algorithm confusing. This article reports the EBMT outcome model. According to the proposed pattern, the system searches for the combination of the instances with the highest probability of the translation instance. The proposed model explicitly manages the EBMTprocess. In addition, standard may contain similar definitions of exemplary definitions. Experimental results show that the proposed model has slightly better interpretation than state-of-the-art EBMT systems.
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Published
2023-05-22
How to Cite
Sapna Thakur and Dr. Priyanka Bhalerao. (2023). Analysis of Probability Model for Example Based Machine Translation. SJIS-P, 35(2), 36–41. Retrieved from http://sjis.scandinavian-iris.org/index.php/sjis/article/view/561
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