学位論文要旨

JAITS＜博士学位論文要旨＞

論文題目: Revising Text: An empirical investigation of revision and the effects ofintegrating a TM and MT system into the translation process（和文タイトル: 修正する翻訳：翻訳プロセスにおける修正行為と、翻訳メモリおよび機械翻訳システムの使用が及ぼす翻訳プロセスへの影響に関する実証研究）
提出者：山田 優
授与機関：立教大学
取得学位の名称：博士（異文化コミュニケーション学）
学位取得の方法：課程
取得年月日：2012 年 3 月 31 日
Abstract
Recent IT development has brought a great deal of change into intercultural and interlingual
communication, resulting in many new forms of translation activities that diverge from those ofconventional translation. In the current GILT (Globalization, Internationalization, Localization, andTranslation) industry, the volume of text to be translated keeps rising, and translators are underpressure to meet restricted costs and tight delivery times. To maximize efficiency, many translatorsand translator-users have turned to computer-assisted translation technologies such as translation
memory (TM) and machine translation (MT).
When TM systems are used, the act of translation is focused on ‘revising the existingtranslation.’ Current machine translation also normally requires human editing of machine-generated
target texts, so-called ‘post-editing.’ Consequently, the role of translators steadily moves away from‘translating’ the source text from scratch to ‘editing’ TM matches or machine translation. Hence, thetranslation process is changed into a series of revision-like operations where revising activities(combinations of other-revision/self-revision) are emphasized, while the traditional activity oftranslating from scratch is minimized.
This shift in emphasis brought about by the use of technology is the main focus of this study
which aims more specifically to investigate the revision processes of translators with different
expertise levels on the one hand, and the way in which TM and MT systems influence translator
behaviors on the other. To this end, the primary research questions have been set as: 1) How
differently do translators with different expertise levels translate (revise) text? and 2) How does theYAMADA Masaru, “Revising text: An empirical investigation of revision and the effects of integrating aTM and MT system into the translation process,” Interpreting and Translation Studies, No.13, 2013. pages
161-164. © by the Japan Association for Interpreting and Translation Studies161『通訳翻訳研究』13 号 (2013)

integration of TM and MT systems affect the translation (revision) process?
The research questions are evaluated through a series of experiments, in which fiveprofessional translators and eighteen students are tasked with translating short texts under different
conditions. This study endeavors partly to make observations on the translation processes oftranslators under natural settings, and partly to assess the effects of integrating TM and MT systems.
The twofold aim of the study is reflected in its experiment design, by which data are collected partly
by a screen recording software program, partly in Trados Translator’s Workbench, a TM system, andpartly in Google Translate/Translator Tool Kit, a statistical machine translation system.
A comparative analysis will be carried out to identify the differences between professionals
and students. In the analysis of the data from Trados Workbench, it will consider how the translation
process will be shaped into a revision-focused activity. The experiments also concerns MT settings,
where translators will perform post-editing of a ‘quasi-text’ that is generated by a statistical machinetranslation.
Apart from the detailed outcomes, the overall results indicate the following. The first researchquestion as to how differently professional and student translators translate in an ordinary translating
setting (human translation setting = HT setting) has been tested through a series of experiments
looking at the variables of time and amount of ‘revision’ activity which in part define text production
styles in translation. The results of revision time occupation under the HT condition showed that thestudents spent proportionally more time on revision than the professionals (44% vs. 24%). The
overall GTM score (General Text Matcher, one of the automatic evaluation metrics that can measure
in-between textual similarities = actual revision amount) in the professional group was 0.938, which
exceeded the average score of the students, 0.771. By comparison, the professionals on average
introduced far fewer modifications (smaller textual changes) than the students under the HT setting.
The experiments found that the students in the HT setting were more revision-oriented translators
than the professionals.
Then the study proceeded to its main interest of uncovering how the integration of a translation
memory system would affect these baseline features of the revision process. When a TM was used,revision activity was generally reduced. The time spent on revision was reduced in both groups. The
professional group spent on average 12.8% of their total translation time on the revision stage, whichshows an almost 50% reduction from the HT case. The results for student translators are similar,
dropping from 44% in the HT case to 19% in the TM case—an almost 50% reduction. The numberof actual revisions also dropped with the reduction in revision. Both professional and student groups
recorded a GTM score of over 0.95. Unsurprisingly, the overall results were in line with those ofprior studies; its time allotment dropped by almost half, and the actual revision amount (textualmodifications) was reduced as well.
It is worth noting, however, that the actual revision amount in the professional group in this162

学位論文要旨

experiment did not show a significant decrease between the HT and TM cases. In other words, while
the students underwent a more drastic shift in translation style from being revision-centered (HT) tovery draft-oriented (TM), the professionals kept their original ‘draft-oriented’ style consistentthrough changes of environment. On the surface, it can be concluded from this observation that theintegration of a translation memory reduces students’ revision activity, but does not alter
professionals’ production style.
However, it was also found that the professionals’ baseline translation speed (in the HT) was
still faster than the speed of the students using a TM, and that they even achieved the same rate ofproductivity gain as the students. Therefore, one may speculate that those professionals seemed tohave acquired an optimal way to maximize efficiency while working with a TM. That is to say,professionals who are highly experienced in the localization industry and translation-aided
technology have stabilized their production style across all translating conditions by adjusting toTM-constrained environments. Over the 20 years since the advent of translation memory systems
and experience in the localization industry, professional translators have been trained to be
draft-oriented translators. This production style maximizes both adaptability to the TM/MT
environment and compliance to the localization context. By condensing their text production work in
the drafting phase, these translators minimize their revision work, leaving it for the independent post
step of other team members, such as dedicated quality reviewers, who are working on the same
localization project.
A next possible change that will exercise an influence on the draft phase in the translation
process will be brought by machine translation (MT) or, to be more precise, MT plus post-editing.
Indeed, when MT post-editing is implemented as a translation assistance strategy, human translators
are aided with proposed ‘quasi-texts’ that are generated by the MT. This new form of translating
activity will in turn bring up a question that concerns the acceptance of machine-translated texts, andhow much human effort is necessary to improve such imperfect texts. If the quality of the raw MT
output is high enough, the amount of revision effort will in theory be reduced, and vice versa.
Sometimes, though, it is easier to translate the source from scratch than to edit the MT output. For
translators, therefore, to revise the MT output or not will be the question.
This question of acceptance of MT output has been evaluated in this study in terms ofproductivity gain and compared to the threshold point at which the raw MT output will (not) support
increased translation speeds, as seen in the TM operation. Translation technology is normally used in
the IT localization field where productivity and efficiency are highly valued; thus, the analysis of theacceptance of MT post-editing was carried out based on these values.
The present research has found that translators seem to prefer modifying the MT output, rather
than translating the source text from the beginning, if the quality of the MT output has a GTM scoreof 0.464 or higher, the same level of effort that is required for modifying TM below-70% matches. It163

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was found that revising MT-generated texts with a GTM above 0.483 results in translators having amore relaxed cognitive load as well as faster translation speed. In simulating a real-life professionalsetting in the case of English-Japanese translation, however, the mean GTM score the current
statistical machine translation (SMT) can render is approximately 0.353. With the score being below
the assumed threshold, the professional translators in the experiment did not feel it advantageous toswitch their production style to its MT post-editing mode. From these results, it was established thatMT post-editing of English-Japanese translations has not yet reached the point at which professionaltranslators can experience ease of task and achieve faster speeds.
However, the localization of certain text types is steadily approaching practical use. SMT has
raised the quality of translation very rapidly with its fast-growing corpora size. The size of aligned(comparable) corpora has been increasing daily through the Internet and networked translation
memory. At its current rate of increase, the SMT can reach the threshold point of GTM 0.464 fromits current level of GTM 0.353 within two to three years.
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【著者紹介】山田 優（YAMADA Masaru）立教大学大学院異文化コミュニケーション研究科博士後期課程修了。異文化コミュニケーション学博士。通訳翻訳学専攻。麗澤大学、青山学院大学、神戸女学院大学、立教大学で講師を務める。

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