Sequence to sequence neural network models for transliteration
Transliteration is a key component of machine translation systems and software internationalization. This paper demonstrates that neural sequence to sequence models obtain state of the art or close to state of the art results on existing datasets. In an effort to make machine transliteration accessible, we open source a new Arabic to English transliteration dataset and our trained models.
ArXiv