The Efficacy of Human Post-Editing for Language Translation(1)

The Efficacy of Human Post-Editing for Language Translation
機譯後人工編輯的功效
Spence Green, Jeffrey Heer, and Christopher D. Manning
Computer Science Department, Stanford University
{spenceg,jheer,manning}@stanford.edu

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Abstract
Language translation is slow and expensive, so various forms of machine assistance have been devised. Automatic machine translation systems process text quickly and cheaply, but with quality far below that of skilled human translators. To bridge this quality gap, the translation industry has investigated post- editing, or the manual correction of machine output. We present the first rigorous, controlled analysis of post-editing and find that post-editing leads to reduced time and, surprisingly, improved quality for three diverse language pairs (English to Arabic, French, and German). Our statistical models and visualizations of experimental data indicate that some simple predictors (like source text part of speech counts) predict translation time, and that post-editing results in very different interaction patterns. From these results we distill implications for the design of new language translation interfaces.
摘要
由於人工翻譯速度慢且價格貴，不同型別的機器輔助工具應運而生。自動機器翻譯系統可以低價快速處理文字，但是翻譯質量卻遠不如翻譯水平較高的人工譯文。為了提高機器翻譯的質量，翻譯行業引入了“譯後編輯”的概念，即對機器翻譯的譯文進行人工修正。本文首次進行了針對譯後編輯的嚴格控制分析，發現譯後編輯可節約時間、極大程度提高三種語言對（英語到阿拉伯語、英語到法語和英語到德語）的翻譯質量。我們的統計模型和實驗資料的視覺化分析結果證明一些簡單的（......）。從這些實驗結果中我們提出了針對新式翻譯介面設計的一些啟示。 （翻譯難度較大，還在斟酌中......）