本文選題：機器翻譯 + 人工評價　； 參考：《廣東外語外貿大學》2017年碩士論文

【摘要】：機器翻譯研究發(fā)展迅速已歷經數個重要階段。它從早期的基于規(guī)則的方法發(fā)展到基于實例的方法再到統(tǒng)計方法。而機器翻譯的翻譯評價一直是其中一個活躍的領域。該領域有令人鼓舞的成果,但困難依然存在。自動評價標準不夠準確,而翻譯質量評估的標準也難以適應機器翻譯的質量評價。該論文提出了機器翻譯的人工評價模型,旨在解決以上的問題。已有的統(tǒng)計機器翻譯的評價指標要么是僅僅從詞語選擇和詞語順序方面評價譯文或者是它們的評價標準呈現相互交疊的情況。該模型包含兩個方面:評價指標、評價指標的權重。評價指標有三個:信息性、語法性、語言多樣性。該模型的構建基于系統(tǒng)思想理論,一個完整的系統(tǒng)應包含組成元素、相互關系、以及組合成后的系統(tǒng)的復雜性。該論文由組成元素對于系統(tǒng)的意義推導出譯文評價的信息性指標,由相互關系對于系統(tǒng)的意義推導出譯文評價的語法性指標,以及同理可得的語言多樣性指標。評價指標的權重反映了每個指標之間的相對重要性的關系。在對模型的有效性進行測試中,本文選取了具有代表性的兩個機器翻譯系統(tǒng):谷歌翻譯和百度翻譯。同時,該測試還在新聞,經濟和體育三個領域隨機選取了30個漢語句子,作為翻譯原文本。得出的譯文將由Asiya(開放在線機器翻譯評價軟件)上面的METEOR進行打分,同時也將由人工評價模型進行打分。該論文分析比較了由兩種評價工具所得的分數結果:METEOR和人工評價模型在評價結果上是一致的。進一步的分析得出人工評價模型的分數結果比METEOR的更加穩(wěn)定,人工評價模型的分數結果的變異系數是6.58%,METEOR的變異系數是29.1%。因此,該人工評價模型能夠提高機器翻譯質量評價的準確性。同時,該模型因為評價指標本身可以量化的特點,所以能夠將該模型應用到機器翻譯系統(tǒng)的自動評價標準里,提升評價準確性,幫助不斷改善機器翻譯的譯文質量。
[Abstract]:The rapid development of machine translation research has gone through several important stages. It developed from the early rule-based approach to the case-based method and then to the statistical method. The translation evaluation of machine translation has always been an active field. There have been encouraging results in this area, but difficulties remain. The automatic evaluation criteria are not accurate enough, and the translation quality assessment criteria are difficult to adapt to machine translation quality evaluation. In this paper, a manual evaluation model of machine translation is proposed to solve the above problems. The existing evaluation criteria of statistical machine translation are either evaluated only in terms of word selection and word order or their evaluation criteria overlap with each other. The model includes two aspects: the evaluation index and the weight of the evaluation index. There are three evaluation indicators: informational, grammatical and linguistic diversity. The model is based on the theory of system theory. A complete system should include the elements, the relationship, and the complexity of the combined system. In this paper, the information index of translation evaluation is derived from the meaning of component elements to the system, the grammatical index of translation evaluation and the linguistic diversity index are derived from the meaning of interrelation to the system. The weight of the evaluation index reflects the relative importance of each index. In order to test the validity of the model, this paper selects two representative machine translation systems: Google Translation and Baidu Translation. At the same time, the test also randomly selected 30 Chinese sentences in news, economics and sports as the original text. The resulting translation will be scored by Meter on Asiya (Open online Machine Translation Evaluation Software) and by a manual evaluation model. This paper analyzes and compares the score results obtained by two evaluation tools: Meter and the artificial evaluation model in the evaluation results are consistent. Further analysis showed that the score of artificial evaluation model was more stable than that of Meter. The coefficient of variation of the score of artificial evaluation model was 6.58 and the coefficient of variation of METEOR was 29.1. Therefore, the artificial evaluation model can improve the accuracy of machine translation quality evaluation. At the same time, the model can be applied to the automatic evaluation standard of machine translation system because of the quantifiable characteristics of the evaluation index itself, so it can improve the accuracy of evaluation and help to improve the translation quality of machine translation.
【學位授予單位】：廣東外語外貿大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：H085

【參考文獻】

相關期刊論文 前5條

1 馬紅霞,錢兆華;20世紀系統(tǒng)思想發(fā)展的回顧[J];系統(tǒng)辯證學學報;2003年01期

2 張華夏;論系統(tǒng)思想——走向21世紀的系統(tǒng)辯證哲學思潮[J];系統(tǒng)辯證學學報;1998年03期

3 馮志偉;機器翻譯——從實驗室走向市場[J];語言文字應用;1997年03期

4 閻德勝;俄漢翻譯與系統(tǒng)思想[J];外語學刊(黑龍江大學學報);1995年03期

5 劉文海;論系統(tǒng)思想[J];中國社會科學院研究生院學報;1993年04期

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本文編號：2036481