互動式機器翻譯中介面回饋的效用評估

Evaluating the Effects of Interface Feedback in MT-embedded Interactive Translation

蔡幸霖(Hsing-Lin Tsai)

指導教授 ： 王浩全

國立清華大學/電機資訊學院/資訊工程學系/碩士(2015年)

摘要

目前跨國合作盛行，當使用不同語言的人們需要傳遞訊息進行溝通時，語言隔閡為其中一個待解決的關鍵問題。互動式翻譯可能為一個有用的方式，它讓非專業翻譯人員使用機器翻譯（Machine Translation），重複的修改翻譯輸入以增加整體翻譯品質。其中一個設計上面臨的挑戰是：我們如何協助人與機器翻譯之間的合作。特別是如何提供有關當下機器翻譯品質的回饋，藉以告知使用者是否接續進行對翻譯輸入的編輯動作。
透過一個lab study和一個field study，本論文評估使用不同類別的介面回饋（如反向翻譯（Back Translation）、數值化分數，及擬人化訊息）來表達預估翻譯品質，對使用者所造成的影響。本研究之結果顯示出，使用數值化分數和擬人化訊息對互動式翻譯的益處，且對機器翻譯介面設計和協助跨語言溝通有所幫助。研究結果也發現，不是所有種類的擬人化回饋皆有助益。表達出正面情緒的擬人化文字能夠給人們較好的使用經驗，而表達出負面情緒的擬人化文字能夠提升翻譯品質。但在擬人化的表情圖片中並沒有獲得其他效用。

關鍵字

互動式介面 ； 機器翻譯

並列摘要

Language barrier is one key challenge to global collaboration where people speaking multiple languages have to exchange messages and understand each other. To bridge different languages at a large scale, interactive translation that involves non-experts to iterate the inputs for machine translation (MT) and to enhance the overall quality is potentially helpful. One design challenge is how do we support the collaboration between human workers and MT, especially how to provide feedback of translation quality to inform workers’ subsequent editing actions. In a lab study and a field study, we evaluate the effects of different types of interface feedback (back translation, numeric score of estimated translation quality, and anthropomorphic social messages as a way of MT-worker communication). The results confirm the utility of using numeric score and social messages as feedback, and shed light on the design of MT interface and cross-lingual communication support. The results further show that not all social features are useful. Facial expression does not add value while showing emotional valence tends to increase positive experience and perception of the work (with positive emotional cues) or improve the quality of translation (with negative emotional cues).

參考文獻

[2] Wang, H.C., Fussell, S.R., Cosley, D. Machine Translation vs. Common Language: Effects on Idea Exchange in Cross-Lingual Groups. Proceedings of CSCW, 2013.

[4] Green, S., Heer, J., and Manning, C.D. The Efficacy of Human Post-Editing for Language Translation. Proceedings of CHI, 2013.

[5] Hu, C., Benderson, B.B, and Resnik, P. Translation by Iterative Collaboration between Monolingual Users. Graphics Interface Conference, 2010.

[7] Albrecht,J.,Hwa,R.,andMarai,G.E.TheChinese Room: Visualization and Interaction to Understand and Correct Ambiguous Machine Translation. Computer Graphics Forum, 28(3), 2009.

[8] Hu, C., Benderson, B.B, Resnik, P., and Kronrod, Y. MonoTrans2: A New Human Computation System to Support Monolingual Translation. Proceedings of CHI, 2011.