/multiDDS

Code for the paper "Balancing Training for Multilingual Neural Machine Translation, ACL 2020"

Primary LanguagePythonMIT LicenseMIT

Balancing Training for Multilingual Neural Machine Translation

Implementation of the paper

Balancing Training for Multilingual Neural Machine Translation

Xinyi Wang, Yulia Tsvetkov, Graham Neubig

Data:

The preprocessed and binarized data for fairseq can be downloaded here

To process data from scrach, see the script

util_scripts/prepare_multilingual_data.sh

Training Scripts:

The training scripts for many-to-one translation of the related language group (Related M2O) is under the directory job_scripts/related_ted8_m2o/.

Our methods:

MultiDDS-S:

job_scripts/related_ted8_m2o/multidds_s.sh

MultiDDS:

job_scripts/related_ted8_m2o/multidds.sh

Baselines:

Proportional:

job_scripts/related_ted8_m2o/proportional.sh

Temperature:

job_scripts/related_ted8_m2o/temperature.sh

The scripts for Related O2M is under the directory job_scripts/related_ted8_o2m/

The scripts for Diverse M2O is under the directory job_scripts/diverse_ted8_m2o/

The scripts for Diverse O2M is under the directory job_scripts/diverse_ted8_o2m/

Inference Scripts:

Each of the experiment script directory contains a trans.sh file to translate the test set. To translate the test set for the Related M2O MultiDDS-S

job_scripts/related_ted8_m2o/trans.sh checkpoints/related_ted8_m2o/multidds_s/

To translate other experiment, simply replace the argument with the experiment checkpoint directory.

Citation

Please cite as:

@inproceedings{wang2020multiDDS,
  title = {Balancing Training for Multilingual Neural Machine Translation},
  author = {Xinyi Wang, Yulia Tsvetkov, Graham Neubig},
  booktitle = {ACL},
  year = {2020},
}