中文全词消歧在机器翻译系统中的性能评测

Evaluation of All-words WSD for Chinese in Machine Translation

独立的词义消歧模型性能已经获得很大提高,但是对于独立消歧模型布机器翻译系统中应用的必要性和作用一直存在着不同的观点.为了从更为一般性的角度评价这个问题,本文突破了具体模型的限制,通过在不同类型汉英机器翻译系统中引入不受特定条件约束的高精度全词消歧过程,对词义消歧在机器翻译系统中的影响进行了较为充分和全面的评价.实验结果证明词义消歧模型不仅本身具有一定的翻译能力,而且可以提高不同类型的机器翻译系统的整体性能.同时也说明当前的翻译系统在消歧能力上还有较大的提升空间.

Although remarkable improvements have been seen in the independent word sense disambiguation （WSD） models, there are still debates about the necessity to integrate the WSD models with the machine translation （MT） systems. To settle the question in a general view, we break the restrictions from specific models and a simulative perfect all-words WSD process is imported into MT systems of different types to acquire a sufficient and general evaluation. Experiment results indicate that a fine WSD process not only yields considerable translation quality itself but also obviously improves the MT systems. In addition, this work also reveals that current MT technologies still have much room to improve in selecting the best translation.