國立臺灣師範大學博碩士論文全文系統

簡易檢索 / 詳目顯示

回結果列表

研究生：	李家璿 Jason Lee
論文名稱：	全自動機器翻譯加後編輯與人工翻譯之比較 A Comparative Study of Fully Automatic Machine Translation with Post-editing and Human Translation
指導教授：	廖柏森 Liao, Po-Sen
學位類別：	碩士 Master
系所名稱：	翻譯研究所 Graduate Institute of Translation and Interpretation
論文出版年：	2010
畢業學年度：	98
語文別：	英文
論文頁數：	110
中文關鍵詞：	機器翻譯、學生翻譯、後編輯、Google Translate
英文關鍵詞：	machine translation, student translation, post-editing, Google Translate
論文種類：	學術論文
相關次數：	點閱：214 下載：56
分享至:	分享至facebook 分享至twitter

查詢本校圖書館目錄查詢臺灣博碩士論文知識加值系統勘誤回報

日新月異的科技演進已大幅改進機器翻譯（MT）的品質，讓機器翻譯成為從事翻譯時的輔助工具。然而，目前鮮少研究比較人工翻譯與自動機器翻譯系統加後編輯，應為一個值得研究的課題。此研究請修習翻譯課程的兩組大學生翻譯一段手機保養指南，文本為英翻中，兩組學生的語言程度具差異；兩組中一部份學生只拿到原文，另一部份學生則多了機器翻譯的譯文可進行後編輯。考量機器翻譯使用便利性及免付費，故譯文取自Google Translate。此研究計算共140位學生翻譯所花費的時間，並利用錯誤分析評估譯文準確性。統計結果顯示，有機器翻譯的譯文能夠顯著減少學生的翻譯錯誤，且使用機器翻譯能縮減學生語言程度的落差。除此之外，質性分析進一步指出學生如何使用機器翻譯譯文，以及不同組別之間的差異。此機器翻譯後端的分析提供人類輔助機器翻譯的實際應用，也點出學生翻譯上的問題。

With advances in technology, many improvements have been made to make machine translation (MT) a tool for human translators that might actually aid in the process of translation. An important issue that has not been extensively investigated is the possible efficient use of available automatic MT systems with post-editing in comparison to human translation. In this study, a cell phone care instruction guide, in need of English to Chinese translation, was given to two groups of college students of different language proficiency levels taking translation classes, where, in each group, some students received only the source text while others received the source text in addition to machine translated text for post-editing. Google Translate was the MT system used in this study for its features of free and easy accessibility. A total of 140 student subjects were timed for their translation task and the accuracy was determined by the number of errors in the translated text. The statistical results indicate the MT text is very helpful in lowering the errors in students’ translation, where the use of MT shortens the gap between students of divergent language proficiency. Further qualitative analysis elucidates how the MT text is utilized and the differences among the two groups of students. This back-end analysis of the machine translation process may offer insights into practical use of human-assisted machine translation, as well as problems encountered by students when translating.

Introduction .................................................................................................................... 1
1.1 General background ......................................................................................... 1
1.2 Research purpose and questions ...................................................................... 3
1.3 Overview of the thesis ..................................................................................... 4
Literature Review........................................................................................................... 6
2.1Machine translation ........................................................................................... 6
2.2 How do people perceive MT? .......................................................................... 9
2.3 MT in the real world ...................................................................................... 11
2.4 Post-editing of MT output .............................................................................. 14
2.5 Error analysis for accuracy assessment .......................................................... 17
2.6 Computer-assisted translation (CAT) and MT in the classroom ................... 23
Research Method ......................................................................................................... 29
3.1 Subjects .......................................................................................................... 29
3.2 The experiment .............................................................................................. 30
3.3 Translation material and text readability ....................................................... 32
3.4 Translation tool—Google Translate .............................................................. 33
3.5 Quantitative and qualitative analysis ............................................................. 36
Results and Discussion ................................................................................................ 38
4.1 Time spent on translation ............................................................................... 38
4.2 Accuracy assessment ..................................................................................... 41
4.2.1 Error comparisons ............................................................................... 41
4.2.2 Ratio of binary and non-binary errors (B/N ratio) .............................. 44
4.3 Word count analysis ....................................................................................... 48
4.3.1 Percentage of MT text used in translation .......................................... 48
4.3.2 The relationship between the percentage of MT use and accuracy .... 49
4.4 The relationship between the time spent on translation and accuracy ........... 51
4.5 The results of questionnaire survey ............................................................... 53
4.6 Qualitative analysis ........................................................................................ 56
4.6.1 Analysis by sentences ......................................................................... 56
4.6.2 Comparison between With MT and No MT students ......................... 59
4.6.3 Language proficiency .......................................................................... 64
4.6.4 Word choice ........................................................................................ 67
4.6.5 Use of the MT text .............................................................................. 71
4.6.6 Constraints by MT text ....................................................................... 78

Conclusions .................................................................................................................. 80
5.1 Major research findings ................................................................................. 80
5.1.1 Translation time .................................................................................. 80
5.1.2 Translation accuracy ........................................................................... 80
5.1.3 Word count analysis ............................................................................ 81
5.1.4 Qualitative findings ............................................................................. 82
5.2 Research implications for using MT in the classroom ........................... 83
5.3 Limitations of this study and suggestions for future works ................... 84
References .................................................................................................................... 86
Appendix ...................................................................................................................... 95
Appendix A (1): The With MT text ..................................................................... 95
Appendix A (2): The No MT text ........................................................................ 96
Appendix B: The vocabulary list ......................................................................... 97
Appendix C(1): The questionnaire (Chinese original) ......................................... 98
Appendix C(2): The questionnaire (English translation) ..................................... 99
Appendix D (1): Raw data of No MT set in Group I ......................................... 100
Appendix D (2): Raw data of With MT set in Group I ...................................... 102
Appendix D (3): Raw data of No MT set in Group II ....................................... 104
Appendix D (4): Raw data of With MT set in Group II .................................... 106
Appendix E: Google Translate MT text at different time points ....................... 107
Appendix F: Sample page of word count by hand ............................................. 109
                                

Ahrenberg, L., & Merkel, M. (1996). On Translation Corpora and Translation Support Tools: A Project Report. In A. Bengt & J. Mats (Eds.), Languages in Contrast (pp. 183-200). Lund: Lund University Press.
Allen, J. (2001). Post-editing or no post-editing? International Journal for Language and Documentation (8), 41-42.
Allen, J. (2003). Post-editing. In H. Somers (Ed.), Computers and Translation: A Translator's Guide. (pp. 297-317). Amsterdam & Philadelphia: Benjamins.
Allen, J. (2004). Case Study: Implementing MT for the Translation of Pre-sales Marketing and Post-sales Software Deployment Documentation (pp 1-6). Paper presented at the 6th Conference of the Association for Machine Translation in the Americas, AMTA 2004, Washington, DC, USA
ALPAC. (1966). Languages and Machines. Computers in Translation and Linguistics. A report by the Automatic Language Processing Advisory Committee, Division of Behavioral Sciences, National Academy of Sciences, National Research Council. Washington, D.C.: National Academy of Sciences, National Research Council
Arnold, D. J., Balkan, L., Meijer S., Humphreys, R.L. & Sadler, L. (1994). Machine translation: an introductory guide. London: Blackwells-NCC.
Aymerich, J. (2005). Using Machine Translation for fast, inexpensive, and accurate health information assimilation and dissemination. Paper presented at the 9th World Congress on Health Information and Libraries. Salvador, Bahia, Brazil.
Banerjee, S., & Lavie, A. (2005). METEOR: An Automatic Metric for MT Evaluation with Improved Correlation with Human Judgments. Paper presented at the Workshop on Intrinsic and Extrinsic Evaluation Measures for MT and/or Summarization at the 43rd Annual Meeting of the Association of Computational Linguistics, Ann Arbor, Michigan.
Bowker, L. (2002). Why Do Translators Need to Learn about Technology? Computer-Aided Translation Technology: A Practical Introduction (pp. 11-21). Ottawa: University of Ottawa Press.
Burgett, W., & Chang, J. (2008). The triple advantage factor of machine translation: cost, time-to-market and FAUT. Paper presented at the Eighth Conference of the Association for Machine Translation in the Americas, Waikiki, Hawaii.
Chan, Y. S., & Ng, T. H. (2008). MAXSIM: A Maximum Similarity Metric for Machine Translation Evaluation. Paper presented at the Association for Computational Linguistics, Columbus, Ohio, USA.
Chang, P.C., Galley, M., & Manning, C.D.. (2008). Optimizing Chinese Word Segmentation for Machine Translation Performance. Paper presented at the Third Workshop on Statistical Machine Translation, Columbus, Ohio, USA.
Chomsky, N. (1975). The logical structure of linguistic theory. Chicago: University of Chicago Press.
Clifford, R., Granoien, N., Jones, D. A., Shen, W., & Weinstein, C. J. (2004). The Effect of Text Difficulty on Machine Translation Performance -- A Pilot Study with ILR-Rated Texts in Spanish, Farsi, Arabic, Russian and Korean. Paper presented at the 4th International Conference on Language Resources and Evaluation, Lisbon, Portugal.
Cronin, M. (2003). Translation and Globalization. New York & London: Routledge.
Cucchiarini, C. (2002). Euromap HLT Case Study: How HLT Applications Can Lead to Higher Quality Translations at Lower Costs: The Experience of Océ Technologies. Retrieved November 14, 2009, from http://www.hltcentral.org/usr_docs/case_studies/euromap/NL_ocecasestudy_nl.pdf
de Schaetzen, C. (1997). L’enseignement de la terminotique: spécificités et contraintes. Terminologies nouvelles, 17, 14-26.
Doddington, G. (2002). Automatic evaluation of machine translation quality using n-gram co-occurrence statistics. Paper presented at the Human Language Technology Conference, San Diego, California.
Eisele, A., Federmann, C., Uszkoreit, H., Saint-Amand, H., Kay, M., Jellinghaus, M., Hunsicker, S., Herrmann, T., & Chen, Y. (2008). Hybrid machine translation architectures within and beyond the EuroMatrix project. Paper presented at the European Machine Translation Conference, Hamburg, Germany.
Esselink, B. (2000). A Practical Guide to Localization. Amsterdam & Philadelphia: John Benjamins.
Farzindar, A. (2009). Automatic translation management system for legal texts. Paper presented at the Machine Translation Summit XII, Ottawa, Ontario, Canada.
Flournoy, R., & Duran, C. (2009). Machine translation and document localization at Adobe: from pilot to production. Paper presented at the Machine Translation Summit XII, Ottawa, Ontario, Canada.
Fulford, H. (2002). Freelance Translators and Machine Translation: An Investigation of Perceptions, Uptake, Experience and Training Needs. Paper presented at the 6th European Association of Machine Translation Workshop, UMIST, Manchester.
Gaspari, F. (2001). Teaching Machine Translation to Trainee Translators: a Survey of Their Knowledge and Opinions. Paper presented at the MT Summit VIII Workshop on Teaching Machine Translation, Santiago de Compostela, Spain.
Gaspari, F. (2002). Using free on-line services in MT teaching. Paper presented at the 6th EAMT Workshop Teaching Machine Translation, Manchester, UK.
Gross, A. (1992). Limitations of computers as translation tools. In J. Newton (Ed.), Computers in translation – a practical appraisal. London: Routledge.
Guerra, L. (2003). Human Translation versus Machine Translation and Full Post-Editing of Raw Machine Translation Output (Master’s thesis). Dublin City University, Dublin.
Guzmán, R. (2007). Manual MT Post-editing: “if it's not broken, don't fix it!". Translation Journal, 11, 4.
Hale, S., & Campbell, S. (2002). The interaction between text difficulty and translation accuracy. Babel 48(1).
Hatim, B., & Munday, J. (2004). Translation: An Advanced Resource Book. London and New York: Routledge
Heim, M. H., Tymowski, A.W., Avtonomova, A., Bao, C., Brecht, Richard D., & Bukhina, O. (2006). Guidelines for the Translation of Social Science Texts: American Council of Learned Societies
Hutchins, J. (1986). Machine translation: past, present, future. UK: Chichester: Ellis Horwood.
Hutchins, J. (1995). Machine translation: a brief history. In E. Koerner (Ed.), Concise history of the language sciences: from the Sumerians to the cognitivists (pp. 431-445). Oxford: Pergamon Press.
Hutchins, J. (1997). Translation Technology and the Translator. Paper presented at the Eleventh Conference of the Institute of Translation and Interpreting, The Crown Hotel, Crown Place, Harrogate. London.
Hutchins, J. (2005). Example-based Machine Translation: A review and commentary. Machine Translation 19, 197 - 211.
Hutchins, J., & Somers, H.L. (1992). An Introduction to Machine Translation. London: Academic Press, Ltd.
Itagaki, M., Aikawa , T., & He, X. (2007). Automatic Validation of Terminology Translation Consistency with Statistical Method. Paper presented at the MT Summit XI, Copenhagen, Denmark.
Kenny, D. (1999). CAT Tools in an academic environment: What are they good for? Target, 11(1), 65-82.
Kenny, D., & Way, A. (2001). Teaching Machine Translation & Translation Technology: A Contrastive Study. Paper presented at the MT Summit VIII Workshop on Teaching Machine Translation, Santiago de Compostela, Spain.
Kliffer, M. D. (2005). An experiment in MT post-editing by a class of intermediate/advanced French majors. Paper presented at the EAMT 10th Annual Conference, Budapest, Hungary.
Lagoudaki, E. (2006). Translation Memories Survey 2006: Users perceptions around TM use Paper presented at the Translating and the Computer Conference, London, UK.
Lavie, A., Sagae, K. & Jayaraman, S. (2004). The Significance of Recall in Automatic Metrics for MT Evaluation. Paper presented at the AMTA 2004, Washington, DC.
Lewis, D. (1997). Machine Translation in a Modern Languages Curriculum. Computer Assisted Language Learning 10, 255–271.
L'Homme, M.-C. (1999). Apports et limites de l’informatique. In D. Gouadec (Ed.), Formation des traducteurs (pp. 109-121). Paris: La Maison du Dictionnaire.
Lionbridge. (2006). When to Use Machine Translation and what business goals can be achieved: Lionbridge Technologies, Inc.
Liu, Q., Hou, H., Lin, S., & Qian, Y. (2005). Introduction to China's HTRDP Machine Translation Evaluation. Paper presented at the MT Summit X, Phuket, Thailand.
Lopez, A. (2008). Statistical machine translation. ACM Comput. Surv. 40(3): 49.
Mauser, A., Hasan, S. & Ney, H. (2008). Automatic Evaluation Measures for Statistical Machine Translation System Optimization. Paper presented at the Language Resources and Evaluation Conference Marrakech, Morocco.
Nagao, M. (1986). Machine Translation: How Far Can It Go? (N. D. Cook, Trans.): Oxford University Press.
Newton, J. (1992). Introduction and overview. In J. Newton (Ed.), Computers in translation - a practical appraisal. London: Routledge.
NIST. (2008). NIST 2008 Open Machine Translation Evaluation- Official Evaluation Results. Retrieved October 15, 2009, from http://www.itl.nist.gov/iad/mig//tests/mt/2008/doc/mt08_official_results_v0.html
O'Brien, S. (2002). Teaching Post-Editing: A Proposal for Course Content. Paper presented at the 6th EAMT Workshop Teaching Machine Translation, Manchester, UK.
O'Brien, S. (2006). Controlled Language and Post-Editing. Multilingual - Getting Started Guide, 17(7), 19.
Och, F. J. (2005). Statistical Machine Translation: Foundations and Recent Advances. Paper presented at the MT Summit 2005, Phuket, Thailand.
Papineni, K. (2002). Machine translation evaluation: n-grams to the rescue. . Paper presented at the International Conference on Language Resources and Evaluation. Las Palmas de Gran Canaria, Spain.
Pym, A. (1992). Translation Error Analysis and the Interface with Language Teaching. In C. Dollerup, Loddegaard, Anne (Ed.), Teaching Translation and Interpreting: Training, Talent and Experience (pp. 279-288). Amsterdam & Philadelphia: John Benjamins.
Richardson, S. (2007). Microsoft Machine Translation: From Research to Real User. Paper presented at the Machine Translation Summit XI, Copenhagen, Denmark.
Richmond, I. M. (1994). Doing it backwards: Using translation software to teach target-language grammaticality. Computer Assisted Language Learning 7, 65–78.
Robin, T.-G. (2008). Practice Makes Perfect: Intermediate English Grammar for ESL Learners. New York: McGraw-Hill.
Sampaio, G. R. L. (2007). Mastering sight translation skills. Tradução & Comunicação, 17.
Scherf, W. G. (1992). Training, Talent and Technology. In C. L. Dollerup, Anne (Ed.), Teaching Translation and Interpreting: Training, Talent and Experience (pp. 153-160). Amsterdam: John Benjamins.
Schwarzl, A. (1999). The (im)possibilities of machine translation. Frankfurt: Peter Lang.
Shih, C. (2006). Helpful assistance to translators: MT & TM. Taipei: Bookman Books, Ltd.
Shih, C. (2007). Mapping Out Students' Translation Process: An MT-specific Comparative Study. 翻譯學研究集刊(10), 163-190.
Somers, H. (2003). Computers and Translation: A Translator's Guide Amsterdam: Benjamins.
Stix, G. (2006). The elusive goal of machine translation. Scientific American 294, 92-95.
Tanner, A. (2007). Google seeks world of instant translations. Retrieved November. 21, 2009 from http://www.reuters.com/article/idUSN1921881520070328
Van der Meer, J. (2003). The Business Case for Machine Translation. Paper presented at the International Conference Translating and the Computer, London, UK.
Van Slype, G. (1982). Economic aspects of machine translation. In V. Lawson (Ed.), Practical experience of machine translation (pp. 79-93). Amsterdam, New York, Oxford: North-Holland Publishing Company.
Vasconcellos, M., & Bostad, D.A. (1992). Machine translation in a high-volume environment. In J. Newton (Ed.), Computers in translation – a practical appraisal. London: Routledge.
Wagner, E. (1985). Post-Editing SYSTRAN – A Challenge for Commission Translators. Terminologie et. Traduction, 3, 1-7.
Wang, Y., & Waibel, A. (1997). Decoding algorithm in statistical machine translation. Paper presented at the 35th Association for Computational Linguistics Conference, Madrid, Spain.
White, J. (2003). How to evaluate machine translation. In H. Somers (Ed.), Computers and Translation: a translator's guide (pp. 211-244). Amsterdam, Philadelphia: Benjamins B.
Wong, T. M. (2008). Machine translation and evaluation: online systems (Master’s thesis). Department of Chinese, Translation and Linguistics, City University of Hong Kong.
Xiao, R., McEnery, Tony, & Qian, Y. (2006). Passive constructions in English and Chinese: A corpus-based contrastive study. Language in Contrast 6, 109-149.
Yuste Rodrigo, E. (2001). Making MT Commonplace in Translation Training Curricula – Too Many Misconceptions, So Much Potential! Paper presented at the MT Summit VIII Workshop on Teaching Machine Translation, Santiago de Compostela, Spain.
劉敏華、張武昌、林世華、陳碧珠、葉舒白、駱香潔 (2005)。「建立國家翻譯人才評鑑基準之研究」期末報告。
賴慈芸 (2003)。他們走了多遠？――大學部學生、翻譯所學生與專業譯者的翻譯表現比較。第八屆口筆譯教學研討會, 臺北：國立臺灣師範大學。

簡易檢索 / 詳目顯示

相關論文