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Research on Phrase-based Statistical Machine Translation

Author: DiPing
Tutor: ZhouGuoDong
School: Suzhou University
Course: Applied Computer Technology
Keywords: Statistical machine translation Phrase translation probability table C value Phrase tenacity Topic Model
CLC: TP391.2
Type: Master's thesis
Year: 2010
Downloads: 115
Quote: 1
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Abstract


With the rapid development of computer technology , statistical machine translation shows the increasingly broad application prospects . Seen as a phrase -based the phrase statistical machine translation system when taking a phrase often arbitrary continuous word , did not consider the rationality of the phrase , it will produce a large number of redundant phrase . This not only expanded the search space of the system , but also seriously affect the quality of the translation . To solve the above problem , this paper focuses on how to effectively improve the quality of the phrase . This paper analyzes the statistical machine translation principles and technology, and on this basis, constructed a phrase-based statistical machine translation reference system . C value and phrases adhesion of two methods and then use the phrase reasonable score , which build a more effective phrase translation probability table . Experimental results show that the phrase translation probability table is reduced to 78 % when using the C value method , the evaluation index of the translation results BLEU value can be improved to 0.02 ; degree of adhesion to the phrase translation the minimum probability table reduced to 47.5% , the translation results BLEU value can enhance 0.0158 . In addition , this article topic model used in statistical machine translation system . Training to decide on a theme for each phrase distribution , translation the few filter out irrelevant themes phrase , thereby enhancing the translation performance . The experimental results show that , compared with the benchmark system , a topic model allows the BLEU value increased 0.0136 . Finally, the article also phrases topic model and C values ??combine to further reduction in the the reserved phrase validity phrase translation probability table . The experiments show that when the phrase translation probability table is reduced to 57% of the original , there is still a certain improvement of the final value of the BLEU . This study and experiments show that the use of these methods can be effectively reduced and optimize the phrase translation probability table , thereby significantly improving the quality of the translation . Topic model is applied to machine translation is an entirely new experience in the future we will further explore how to better play to the advantage of the topic model in statistical machine translation .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Translator
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