- Google has released a zero-shot translation task through the GNMT model. The project will try to use the new model(Transformer) to perform translation tasks and experiment with the possibility of translating zero-shot through various languages.
- First, You can train your translation model ( Transformer ) using
vanilla_transformer - Second, You can have experiment of Zero-Shot translation using Transformer by
transformer_zero_shot - Figure below this paragraph shows the concept of Zero-Shot translation
preprocessor.pydownload & preprocess data ( you can use OpenSubtitle2018 / MultiUN dataset )data_loader.pydefine class for data load ( Input pipeline developed by tf.dataset)model_layer.pydefine all layer needed for construct transformer modelmodel.pydefine transformer modeltrain.pyfor training modeleval.pyis for evaluation
- STEP 1. Set the configuration by editing
hyperparams.py - STEP 2. Run
preprocessor.py, it will preprocess and make training data - STEP 3. Run
train.pyto train your model - STEP 4. Run
eval.pyto save result and calculate BLEU score
- Ashish Vaswan, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Łukasz Kaiser Illia Polosukhin Attention Is All You Need, arXiv:1706.03762v5, 2017
- Melvin Johnson, Mike Schuster, Quoc V. Le, Maxim Krikun, Yonghui Wu, Zhifeng Chen, Nikhil Thorat , Fernanda Viégas, Martin Wattenberg, Greg Corrado, Macduff Hughes, Jeffrey Dean, Google’s Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation, arXiv:1611.04558v2 2017
- Jörg Tiedemann, 2012, Parallel Data, Tools and Interfaces in OPUS. In Proceedings of the 8th International Conference on Language Resources and Evaluation (LREC 2012)
- P. Lison and J. Tiedemann, 2016, OpenSubtitles2016: Extracting Large Parallel Corpora from Movie and TV Subtitles. In Proceedings of the 10th International Conference on Language Resources and Evaluation (LREC 2016)
- https://github.com/Kyubyong/transformer
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