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    政大機構典藏 > 資訊學院 > 資訊科學系 > 學位論文 >  Item 140.119/32695
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/32695


    Title: 以範例為基礎之英漢TIMSS詴題輔助翻譯
    Using Example-based Translation Techniques for Computer Assisted Translation of TIMSS Test Items
    Authors: 張智傑
    Chang, Chih Chieh
    Contributors: 劉昭麟
    Liu, Chao Lin
    張智傑
    Chang, Chih Chieh
    Keywords: 自然語言處理
    試題翻譯
    機器翻譯
    Natural language processing
    Item translation
    Machine translation
    TIMSS
    Date: 2008
    Issue Date: 2009-09-17 14:04:36 (UTC+8)
    Abstract: 本論文應用以範例為基礎的機器翻譯技術,應用英漢雙語對應的結構輔助英漢單句語料的翻譯。翻譯範例是運用一種特殊的結構,此結構包含來源句的剖析樹、目標句的字串、以及目標句和來源句詞彙對應關係。將翻譯範例建立資料庫,以提供來源句作詞序交換的依據,接著透過字典翻譯,以及利用統計式中英詞彙對列和語言模型來選詞,最後填補缺少的量詞,產生建議的翻譯。我們是以2003年國際數學與科學教育成就趨勢調查測驗詴題為主要翻譯的對象,以期提升翻譯的一致性和效率。以NIST 和BLEU 的評比方式,來評估和比較Google Translate 和Yahoo!線上翻譯系統及本系統所達成的翻譯品質。我們的系統經過詞序調動以及填補量詞後,翻譯品質比我們前一代系統要佳,但整體效果沒有比Google Translate 和Yahoo!線上翻譯的品質要佳。
    This paper presents an example-based machine translation based on bilingual structured string tree correspondence (BSSTC). The BSSTC structure includes a parse tree in source language, a string in target language and the correspondence between the source language tree and the target language string.
    <br>We designed an English to Chinese computer assisted translation system for Trends in International Mathematics and Science Study (TIMSS), through the BSSTC structure reordering, directory translation, choosing translation statistics model and measure word generation.<br>We evaluated our system by the BLEU and NIST score and compared with Google Translate and Yahoo! Translate. By reordering selected word sequences and inserting measure words in the default translations, the current system achieved a higher quality of default translations than the previous implementation of our research group, but the overall effects still lag behind that achieved by Google and Yahoo!.
    Reference: [1] 中研院中文剖析器檢索系統,http://parser.iis.sinica.edu.tw/ [Accessed: Oct. 28, 2008].
    [2] 中研院平衡語料庫詞類標記集,http://ckipsvr.iis.sinica.edu.tw/category_list.doc [Accessed: Oct. 28, 2008].
    [3] 自由時報中英對照讀新聞,http://www.libertytimes.com.tw/2008/new/jan/15/english.htm [Accessed: Jun. 30, 2008].
    [4] 呂明欣,電腦輔助詴題翻譯:以國際數學與科學教育成就趨勢調查為例,國立政治大學資訊科學所,碩士論文,2007。
    [5] 夏敏翔、張耀升和盧文祥,使用流暢性改善詞組翻譯的統計式機器翻譯,第十八屆自然語言與語音處理研討會論文集。台灣,新竹,2006。
    [6] 教育部委託宜蘭縣發展九年一貫課程建置語文學習領域(英語)國中教科書補充資料暨題庫建置計畫,http://140.111.66.37/english/ [Accessed: Oct. 28, 2008].
    [7] M. H. Al-Adhaileh, T. E. Kong and Y. Zaharin, “A synchronization structure of SSTC and its applications in machine translation”, Proceedings of the International Conference on Computational Linguistics -2002 Post-Conference Workshop on Machine Translation in Asia, 1–8, 2002.
    [8] C. Boitet and Y. Zaharin, “Representation trees and string-tree correspondences”, Proceedings of the Twelfth International Conference on Computational Linguistics, 59–64, 1998.
    [9] P. F. Brown, J. Cocke, S. A. D. Pietra, V. J. D. Pietra, F. Jelinek, J. D. Lafferty, R. L. Mercer and P. S. Roossin, “A Statistical Approach to Machine Translation”, Computational Linguistics, 79-85, 1990.
    [10] Concise Oxford English Dictionary, http://stardict.sourceforge.net/Dictionaries_zh_TW.php [Accessed: Oct. 28, 2008].
    58
    [11] G. Doddington, “Automatic evaluation of machine translation quality using n-gram co-occurrence statistics”, Proceedings of the Second International Conference of Human Language Technology Research, 138–145, 2002.
    [12] B. J. Dorr, P. W. Jordan and J. W. Benoit, “A Survey of Current Paradigms in Machine Translation” Advances in Computers, London: Academic Press, 1–68, 1999.
    [13] Google Translate, http://translate.google.com/translate_t [Accessed: Oct. 28, 2008].
    [14] D. Klein and C. Manning, “Accurate Unlexicalized Parsing”, Proceedings of the Forty-first Meeting of the Association for Computational Linguistics, 423–430, 2003.
    [15] K. Knight and S. K. Luk, “Building a large-scale knowledge base for machine translation”, Proceedings of the Twelfth National Conference on Artificial intelligence, 773–778, 1994.
    [16] P. Koehn, F. J. Och and D. Marcu, “Statistical phrase-based translation”, Proceedings of the Human Language Technology Conference, 127–133, 2003.
    [17] R. Levy and C. Manning, “Is it harder to parse Chinese, or the Chinese Treebank?” Proceedings of the Forty-first Conference of the Association for Computational Linguistics, 439–446, 2003.
    [18] Z. Liu, H. Wang and H. Wu, “Example-based Machine Translation Based on TSC and Statistical Generation”, Proceedings of the Tenth Machine Translation Summit, 25–32, 2005.
    [19] F. J. Och, “An Efficient Method for Determining Bilingual Word Classes”, Proceedings of European Chapter of the Association for Computational Linguistics, 71–76, 1999.
    [20] F. J. Och and H. Ney, “Improved Statistical Alignment Models”, Proceedings of the Thirty-eighth Annual Meeting of the Association for Computational Linguistics, 440–447, 2000.
    59
    [21] K. Papineni, S. Roukos, T. Ward, and W. J. Zhu, “Bleu: a method for automatic evaluation of machine translation”, Proceedings of the Fortieth Annual Meeting of the Association for Computational Linguistics, 311–318, 2002.
    [22] The Stanford Parser: A statistical parser, http://nlp.stanford.edu/software/ [Accessed: Oct. 28, 2008].
    [23] A. Stolcke, SRILM – an extensible language modeling toolkit. Proceedings of the intelligence Conference on Spoken Language Processing, 901–904, 2002. http://www.speech.sri.com/projects/srilm/ [Accessed: Oct. 28, 2008].
    [24] S. Sato and M. Nagao, Toward Memory-Based Translation”, Proceedings of International Conference on Computational Linguistics, 247–252, 1990.
    [25] The International Association for the Evaluation of Education Achievement, http://www.iea.nl/ [Accessed: Oct. 28, 2008].
    [26] TIMSS 中文版官方網頁, http://timss.sec.ntnu.edu.tw/timss2007/news.asp [Accessed: Oct. 28, 2008].
    [27] The Porter Stemming Algorithm, http://www.tartarus.org/martin/PorterStemmer/ [Accessed: Oct. 28, 2008].
    [28] WordNet API, http://nlp.stanford.edu/nlp/javadoc/wn/ [Accessed: Oct. 28, 2008].
    [29] F. Wong, M. Dong and D. Hu, Machine Translation Based on Translation Corresponding Tree Structure, Tsinghua Science & Technology, 25–31, 2006.
    [30] YAHOO! 雅虎線上翻譯, http://tw.babelfish.yahoo.com/ [Accessed: Oct. 28, 2008].
    [31] D. Zhang, M. Li, N. Duan, C. H. Li and M. Zhou, “Measure Word Generation for English-Chinese SMT Systems”, Proceedings of Association for Computational Linguistics, 89–96, 2008.
    Description: 碩士
    國立政治大學
    資訊科學學系
    95753012
    97
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0095753012
    Data Type: thesis
    Appears in Collections:[資訊科學系] 學位論文

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