REPROLANG 2020 @ LREC - Task A.1: VecMap, Cross-Lingual Word Embedding Mappings

This is a fork from the original open source implementation of the framework to learn cross-lingual word embedding mappings.

This repository is strictly limited to the reproduction of the original paper of Artetxe et al. 2018 (ACL).

Dataset

• The dataset is available here: https://vecmap-submission.s3.amazonaws.com/dataset.tar.gz
• The checksum of the dataset is: 69409adb48f668ce8872d924caec4519
• Untar the dataset using the following command: tar -xvf dataset.tar.gz

Original paper result reproduction

The reproduction of the Table 1 and 2 of our paper can easily be done using the docker image that we provide.

First, create the output directories on the host. assuming the data have been previously downloaded:

mkdir -p output/tables_and_plots

It is mandatory to have a GPU on the host with NVIDIA Docker. Otherwise the docker image will crash. One can generate the tables with the following command, but its takes about a day to generate all the results;

docker run --gpus all -ti --rm -v ${PWD}/data:/input -v ${PWD}/output/tables_and_plots:/output/tables_and_plots registry.gitlab.com/nicolasgarneau/vecmap 

It is also possible to launch the script in test mode, which is a subset of only 1999 words, using the following command:

docker run --gpus all -ti --rm -v ${PWD}/data:/input -v ${PWD}/output/tables_and_plots:/output/tables_and_plots registry.gitlab.com/nicolasgarneau/vecmap /run.sh "--test=True"

Reproducing all the results of our paper

In our analysis, we presented more results in order to assess the robustness of the algorithm.

To recreate these results, one should parallelize the computation otherwise it will take many days to gather the results.

Using the same docker image that we provide, it is possible to create all the tables and plots with the following command (assuming the directory output/tables_and_plots was previously created);

docker run --gpus all -ti --rm -v ${PWD}/data:/input -v ${PWD}/output/tables_and_plots:/output/tables_and_plots registry.gitlab.com/nicolasgarneau/vecmap /run_all.sh 

It is also possible to launch the script in test mode, as describe previously, using the following command:

docker run --gpus all -ti --rm -v ${PWD}/data:/input -v ${PWD}/output/tables_and_plots:/output/tables_and_plots registry.gitlab.com/nicolasgarneau/vecmap /run_all.sh "--test=True"

Build the Docker image

It is also possible to build the Docker image using the following command:

./build.sh

Publications

If you use this software for academic research, please cite the relevant paper(s) as follows for the original model:

@inproceedings{artetxe2018acl,
  author    = {Artetxe, Mikel  and  Labaka, Gorka  and  Agirre, Eneko},
  title     = {A robust self-learning method for fully unsupervised cross-lingual mappings of word embeddings},
  booktitle = {Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  year      = {2018},
  pages     = {789--798}
}

License

Copyright (C) 2016-2018, Mikel Artetxe

Licensed under the terms of the GNU General Public License, either version 3 or (at your option) any later version. A full copy of the license can be found in LICENSE.txt.