Filtering and Mining Parallel Data in a Joint Multilingual Space

We learn a joint multilingual sentence embedding and use the distance between sentences in different languages to filter noisy parallel data and to mine for parallel data in large news collections. We are able to improve a competitive baseline on the WMT'14 English to German task by 0.3 BLEU by filtering out 25% of the training data... (read more)

PDF Abstract ACL 2018 PDF ACL 2018 Abstract

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper


METHOD TYPE
🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet