Improving translation quality of rule-based machine translation
COLING-MTIA '02 Proceedings of the 2002 COLING workshop on Machine translation in Asia - Volume 16
Measuring efficiency in high-accuracy, broad-coverage statistical parsing
Proceedings of the COLING-2000 Workshop on Efficiency In Large-Scale Parsing Systems
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One challenge of Myanmar-English statistical machine translation system is that the output (translated English sentence) can often be ungrammatical. To address this issue, this paper presents an ongoing grammar checker as a second language by using trigram language model and rule based model. It is able to solve distortion, deficiency and make smooth the translated English sentences. We identify the sentences with chunk types and generate context free grammar (CFG) rules for recognizing grammatical relations of chunks. There are three main tasks to reduce grammar errors: detecting the sentence patterns in chunk level, analyzing the chunk errors and correcting the errors. Such a three level scheme is a useful framework for a chunk based grammar checker. Experimental results show that the proposed grammar checker can improve the correctness of translated English sentences.