Research on the Transformation of Ba-Construction in Patent Machine Translation

2014 ◽  
Vol 513-517 ◽  
pp. 4601-4604
Author(s):  
Wen Fei Chang ◽  
Zhi Ying Liu ◽  
Yao Hong Jin ◽  
Lin Nan Bai ◽  
Hui Ying Yan
Keyword(s):  
Machine Translation ◽  
Critical Issue ◽  
Point Of View ◽  
Utilization Rate ◽  
Translation System ◽  
Ba Construction ◽  
Machine Translation System ◽  
Semantic Point ◽  
Concept Theory ◽  
Action Sentence

Ba-construction is a special structure in Chinese, it has a high utilization rate in patent documents and there is no corresponding sentence in English. Therefore, Ba-construction is a critical issue in machine translation. In this paper, based on the Hierarchical Network of Concept theory (HNC theory), we have an analysis of the Ba-construction in action sentence (XJ) and transfer sentence (TJ), and then conclude 4 main verbs translation formats from the semantic point of view according to corpus. The research results have been applied to our machine translation system and it has improved the correct rate of translation effectively.

English-Dogri Translation System using MOSES

2016 ◽  
Vol 1 (1) ◽  
pp. 45-49
Author(s):  
Avinash Singh ◽  
Asmeet Kour ◽  
Shubhnandan S. Jamwal
Keyword(s):  
Natural Language Processing ◽  
Machine Translation ◽  
Language Processing ◽  
Statistical Machine Translation ◽  
Translation System ◽  
Parallel Corpus ◽  
English System ◽  
Machine Translation System ◽  
Translation Machine ◽  
Language Pair

The objective behind this paper is to analyze the English-Dogri parallel corpus translation. Machine translation is the translation from one language into another language. Machine translation is the biggest application of the Natural Language Processing (NLP). Moses is statistical machine translation system allow to train translation models for any language pair. We have developed translation system using Statistical based approach which helps in translating English to Dogri and vice versa. The parallel corpus consists of 98,973 sentences. The system gives accuracy of 80% in translating English to Dogri and the system gives accuracy of 87% in translating Dogri to English system.

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