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

Understand

Parallel sentence extraction is a task addressing the data sparsity problem found in multilingual natural language processing applications.

• We propose a bidirectional recurrent neural network based approach to extract parallel sentences from collections of multilingual texts.
• Our experiments with noisy parallel corpora show that we can achieve promising results against a competitive baseline by removing the need of specific feature engineering or additional external resources.
• To justify the utility of our approach, we extract sentence pairs from Wikipedia articles to train machine translation systems and show significant improvements in translation performance.