From 0cd9b8bcfb4bc413c29a76611cc65cb3201cb1b4 Mon Sep 17 00:00:00 2001 From: nlpfun Date: Tue, 30 Nov 2021 23:57:55 +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 34eb496..a8b915e 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