Tree-to-String Machine Translation System
Graham Neubig, Kevin Duh · 2014
While tree-to-string (T2S) translation theoretically holds promise for efficient, accurate translation, in previous reports T2S systems have often proven inferior to other machine translation (MT) methods such as phrase-based or hierarchical phrase-based MT. In this paper, we attempt to clarify the reason for this performance gap by investigating a number of peripheral elements that affect the accuracy of T2S systems, including parsing, alignment, and search. Based on detailed experiments on the English-Japanese and JapaneseEnglish pairs, we show how a basic T2S system that performs on par with phrasebased systems can be improved by 2.6-4.6 BLEU, greatly exceeding existing stateof-the-art methods. These results indicate that T2S systems indeed hold much promise, but the above-mentioned elements must be taken seriously in construction of these systems.