Issue #39 – Context-aware Neural Machine Translation
30 May19
Issue #39 – Context-aware Neural Machine Translation
Author: Dr. Rohit Gupta, Sr. Machine Translation Scientist @ Iconic
Back in Issue #15, we looked at the topic of document-level translation and the idea of looking at more context than just the sentence when machine translating. In this post, we will have a look more generally at the role of context in machine translation as relates to specific types of linguistic phenomena and issues related to them. We review the work by Voita et al. (2019) where they observed various issues arising from the absence of context. They also proposed an approach to resolve such issues.
Context Related Issues in English-Russian Translation
To analyse the errors related to contextual information, the Voita et al. translated a test set of 2,000 pairs of consecutive sentences using a baseline transformer model. They used English-Russian as part of the OpenSubtitles data for the test and training the engine. They conducted both evaluation at sentence level and evaluation in context. The authors found that in 7% of the cases, the translations were bad in context even though the individual sentence translations in the pairs were good. In these
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