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@@ -3,7 +3,7 @@ Word Embedding-Based Bilingual Sentence Aligner
Bertalign is designed to facilitate the construction of bilingual parallel corpora, which have a wide range of applications in translation-related research such as corpus-based translation studies, contrastive linguistics, computer-assisted translation, translator education and machine translation.
Bertalign uses the [LaBSE multilingual BERT model](https://arxiv.org/abs/2007.01852) provided by [sentence-transformers](https://github.com/UKPLab/sentence-transformers) to represent source and target sentences so that semantically similar sentences in different languages can be mapped onto similar vector spaces. According to our experiments, Bertalign achieves more accurate results than the traditional length-, dictionary-, or MT-based alignment methods such as [Galechurch](https://aclanthology.org/J93-1004/), [Hunalign](http://mokk.bme.hu/en/resources/hunalign/) and [Bleualign](https://github.com/rsennrich/Bleualign). It also performs better than [Vecalign](https://github.com/thompsonb/vecalign) on MAC, a manually aligned parallel corpus of Chinese-English literary texts.
Bertalign uses the [LaBSE multilingual BERT model](https://arxiv.org/abs/2007.01852) (supporting 109 languages) provided by [sentence-transformers](https://github.com/UKPLab/sentence-transformers) to represent source and target sentences so that semantically similar sentences in different languages can be mapped onto similar vector spaces. According to our experiments, Bertalign achieves more accurate results than the traditional length-, dictionary-, or MT-based alignment methods such as [Galechurch](https://aclanthology.org/J93-1004/), [Hunalign](http://mokk.bme.hu/en/resources/hunalign/) and [Bleualign](https://github.com/rsennrich/Bleualign). It also performs better than [Vecalign](https://github.com/thompsonb/vecalign) on MAC, a manually aligned parallel corpus of Chinese-English literary texts.
## Installation