commit b5fdb0bcdce91354bcce8a4bedfe979b7b763250 Author: vivekvardhanadepu Date: Mon Jun 14 13:34:53 2021 +0530 adding new repo link diff --git a/README.md b/README.md index 4ef0816..1cc3bfe 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,7 @@ # user-friendly-lexical-training +**repo moved to [apertium-lexical-training](https://github.com/vivekvardhanadepu/apertium-lexical-training)** + The procedure for lexical selection training is a bit messy, with various scripts involved that require lots of manual tweaking, and many third party tools to be installed, e.g. irstlm, moses, gizapp. The goal of this task is to make the training procedure as streamlined and user-friendly as possible for more, read https://wiki.apertium.org/wiki/Ideas_for_Google_Summer_of_Code/User-friendly_lexical_selection_training @@ -8,25 +10,25 @@ for more, read https://wiki.apertium.org/wiki/Ideas_for_Google_Summer_of_Code/Us This folder contains scripts for automated testing of the helper scripts -## coding challenges *(using for testing)* +## coding challenges _(using for testing)_ In directory coding_challenges, **Training parallel corpora:** -*(change the relevant paths)* +_(change the relevant paths)_ pre-training: preProcessing.sh lang-models: make_lang_model.sh -alignment: alignment.sh[using fast_align, [Chris Dyer](http://www.cs.cmu.edu/~cdyer), [Victor Chahuneau](http://victor.chahuneau.fr), and [Noah A. Smith](http://www.cs.cmu.edu/~nasmith). (2013). [A Simple, Fast, and Effective Reparameterization of IBM Model 2](http://www.ark.cs.cmu.edu/cdyer/fast_valign.pdf). In *Proc. of NAACL*.] +alignment: alignment.sh[using fast_align, [Chris Dyer](http://www.cs.cmu.edu/~cdyer), [Victor Chahuneau](http://victor.chahuneau.fr), and [Noah A. Smith](http://www.cs.cmu.edu/~nasmith). (2013). [A Simple, Fast, and Effective Reparameterization of IBM Model 2](http://www.ark.cs.cmu.edu/cdyer/fast_valign.pdf). In _Proc. of NAACL_.] rule-extraction: rule_extraction.sh cache-SL-TL: intermediate output files and logs for debugging -**Typical moses training:**(*without using apertium tools*) +**Typical moses training:**(_without using apertium tools_) In moses_training,