Learning Bilingual Sentence Embeddings via Autoencodingand Computing Similarities with a Multilayer Perceptron
Table 1: Sentence alignment recovery results. Our method results use cosine similarity except the last row.
['Method', 'Error [%] WMT', 'Error [%] IWSLT']
The Levenshtein distance gives a poor performance. NMT models are better than the other methods, but takes too long to compute posteriors for all possible pairs of source and target sentences (about 12 hours for the WMT test set). This is absolutely not feasible for a real mining task with hundreds of millions of sentences.