神經機器翻譯於時尚網站在地化之應用

Applying Neural Machine Translation to Fashion Website Localization

廖亭雲(Ting-Yun Liao)

指導教授 ： 高照明

國立臺灣大學/文學院/翻譯碩士學位學程/碩士(2019年)

https://doi.org/10.6342/NTU201903661

摘要

隨著網路使用人口成長，網站在地化的需求也持續增加，而為了以更快速度提供品質穩定的翻譯成果，將自動翻譯融入在地化專案原有的工作流程已是必然趨勢。另一方面，近年來由於網路發展迅速讓語料庫取得更加容易，也促進了機器翻譯技術的發展，實現自訂神經機器翻譯模型的應用。然而目前自訂神經機器翻譯的相關研究多半仍集中在改善技術層面，因此本研究將會將重心放在將自訂神經機器翻譯系統應用於在地化專案，並且採用自動化方法與專業譯者參與實驗的方式評估其效能與效果。在建立自訂神經機器翻譯系統方面，本研究從風格類似的三個快時尚品牌網站中，分別擷取出繁體中文與英文的產品介紹文字檔，彙整成雙語平行語料庫，再將母語料庫分為訓練與驗證兩個語料庫，用於訓練與檢驗自訂神經機器翻譯系統。而除了採用自動化方法衡量機器翻譯的效能，本研究也招募專業譯者參與模擬實際在地化專案的實驗，比較自訂機器翻譯與一般機器翻譯的效果。研究結果顯示，本研究建立的自訂神經機器翻譯經過自動化方法評估可達到良好效能，而在專業譯者的使用者經驗方面，自訂神經機器翻譯確實有一定的效果，能協助提升譯者的工作效率。儘管本研究指出將神經機器翻譯應用於在地化專案的可行性，由於研究中選擇的語料僅侷限在快時尚購物網站，研究結果可能無法在其他在地化領域上成立，而適用於其他翻譯領域的自訂神經機器翻譯系統則需要將來進一步的研究。

關鍵字

神經機器翻譯 ； 在地化 ； 電腦輔助翻譯 ； 平行語料庫

並列摘要

As the number of internet users grows around the world, the demand for website localization also increases. To meet this ever-growing need, a trend has inevitably formed where automatic translation is being integrated into the workflow of localization. In recent years, the development of the internet has provided easy access to various corpora, which advances the technology of machine translation and, in turn, realizes the application of customized neural machine translation (NMT). Nevertheless, previous studies on customized NMT usually center on improving the technology itself. Thus, this research focuses on applying a customized NMT to website localization and validating its performance and effects with automatic evaluation and an experiment involving human translators. To build customized NMT, the bilingual text from shopping websites including H&M, ZARA and Burberry is compiled into a parallel corpus, which is divided into two separate corpora which train and evaluate the customized NMT. In addition to automatic evaluation, this study also carries out an experiment aiming to compare the effectiveness of the customized NMT and that of general MT which was modeled on real localization projects which involved professional translators,. The automatic evaluation result indicates that the NMT built in this research performs well. Moreover, based on the feedback from translators participating in this study, the customized NMT does exhibit positive effects on increasing translation efficiency. Due to the fact that the corpus used in this research is limited to a specific domain, the results might not be applicable to other localization fields, and further research is needed to investigate the effectiveness of customized NMT in other domains.

並列關鍵字

neural machine translation ； localization ； computer-aided translation ； parallel corpora

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