From 16aa1b6bad7256445ab5044d5428bd5612bd4f58 Mon Sep 17 00:00:00 2001 From: nlpfun Date: Tue, 30 Nov 2021 23:57:14 +0800 Subject: [PATCH] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 2f2ab55..34eb496 100644 --- a/README.md +++ b/README.md @@ -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 models](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 models](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. ## Installation