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Parallel sentence extraction is a task addressing the data sparsity problemfound in multilingual natural language processing applications. We propose abidirectional recurrent neural network based approach to extract parallelsentences from collections of multilingual texts. Our experiments with noisyparallel corpora show that we can achieve promising results against acompetitive baseline by removing the need of specific feature engineering oradditional external resources. To justify the utility of our approach, weextract sentence pairs from Wikipedia articles to train machine translationsystems and show significant improvements in translation performance.

Extracting Parallel Sentences with Bidirectional Recurrent Neural Networks to Improve Machine Translation