Improving Performance of Transfer-Driven Machine Translation with Extra-Linguistic Informatioon from Context, Situation and Environment
نویسندگان
چکیده
This paper describes an improvement in the performance of Transfer-Driven Machine Translation ( T D M T ) by the use of extralinguistic information. In evaluating what constitutes natural speech, particular attention was paid to word usage that depended on the extra-linguistic information from the context, situation, environment and so on. We discuss what types of extra-linguistic information a spoken-language translation system requires to create naturally communicative dialogs. We then propose a method of improving the precision of translation by utilizing this extralinguistic information. Preliminary experimentation showing performance improvements in T D M T makes us believe that the proposed scheme can improve the performance of dialog M T .
منابع مشابه
The Influence of Data-Driven Exercises Through Using a Computer Program on Vocabulary Improvement in an EFL Context
The present study was conducted to evaluate data driven learning (DDL) combined with Computer Assisted Language Learning (CALL) as an approach to improving vocabulary knowledge of Iranian postgraduates majoring in teaching English, English literature and translation. The purpose was to help language learners get familiar with DDL as a student-centered method taking advantage of a computer progr...
متن کاملThe Influence of Data-Driven Exercises Through Using a Computer Program on Vocabulary Improvement in an EFL Context
The present study was conducted to evaluate data driven learning (DDL) combined with Computer Assisted Language Learning (CALL) as an approach to improving vocabulary knowledge of Iranian postgraduates majoring in teaching English, English literature and translation. The purpose was to help language learners get familiar with DDL as a student-centered method taking advantage of a computer progr...
متن کاملHow to Avoid Burning Ducks: Combining Linguistic Analysis and Corpus Statistics for German Compound Processing
Compound splitting is an important problem in many NLP applications which must be solved in order to address issues of data sparsity. Previous work has shown that linguistic approaches for German compound splitting produce a correct splitting more often, but corpus-driven approaches work best for phrase-based statistical machine translation from German to English, a worrisome contradiction. We ...
متن کاملHow to Avoid Burning Ducks: How to Avoid Burning Ducks: Combining Linguistic Analysis and Corpus Statistics for German Compound Processing
Compound splitting is an important problem in many NLP applications which must be solved in order to address issues of data sparsity. Previous work has shown that linguistic approaches for German compound splitting produce a correct splitting more often, but corpus-driven approaches work best for phrase-based statistical machine translation from German to English, a worrisome contradiction. We ...
متن کاملTransfer-Driven Machine Translation
Transfer-Driven Machine Translation (TDMT) [1, 2] is a translation technique developed as a research project at ATR Interpreting Telecommunications Research Laboratories. In TDMT, translation is performed mainly by a transfer module which applies transfer knowledge to an input sentence. Other modules, such as lexical processing, analysis, contextual processing and generation, cooperate with the...
متن کامل