Translating Negation: A Manual Error Analysis
Translating Negation: A Manual Error Analysis
复制标题
翻译否定：手动错误分析
DOI：
10.3115/v1/w15-1301
复制
发表时间：
2015
期刊：
影响因子：
--
通讯作者：
B. Webber
中科院分区：
文献类型：
--
作者：
Federico Fancellu;B. Webber
统计机器翻译已经取得了长足的进步，提高了一系列不同语言现象的翻译质量。然而，对于否定，为提高翻译性能而提出和实施的技术只是遵循了开发人员关于为什么性能更差的信念。然而，这些信念从未通过对翻译输出的错误分析得到验证。相比之下，当前的论文表明，信息丰富的经验错误分析可以用(1)否定意义中涉及的一组语义元素，以及(2)一小组基于字符串的操作来表述，这些操作可以表征这些元素翻译中的错误。一个汉英翻译任务的结果证实了我们跨语言分析的稳健性，并且基本假设可以为自动调查翻译错误的原因提供信息。分析得出的结论可以指导今后否定句翻译的改进工作。
Statistical Machine Translation has come a long way improving the translation quality of a range of different linguistic phenomena. With negation however, techniques proposed and implemented for improving translation performance on negation have simply followed from the developers’ beliefs about why performance is worse. These beliefs, however, have never been validated by an error analysis of the translation output. In contrast, the current paper shows that an informative empirical error analysis can be formulated in terms of (1) the set of semantic elements involved in the meaning of negation, and (2) a small set of string-based operations that can characterise errors in the translation of those elements. Results on a Chinese-to-English translation task confirm the robustness of our analysis cross-linguistically and the basic assumptions can inform an automated investigation into the causes of translation errors. Conclusions drawn from this analysis should guide future work on improving the translation of negative sentences.