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DataExploration.ipynb
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LanguageModel.py
README.md
ScorePrinter.py
decoder.py
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multi_bleu.pl
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validation.ipynb

README.md

Attentional Neural Machine Translation

Scope

Standard attentional-based NMT framework (Bahdanau et al. 2014)

  • Data Preparer
  • (Bidirectional) GRU/LSTM-based encoder
  • Global Attention Layers: MLP/Dot Product (Luong et al. 2015)
  • GRU/LSTM-based decoder
  • Beam Search
  • Teacher Forcing

Requirements

  • Data Preparation: Convert words to index prior to one-hot encoding for training, validation and test sets.
  • Training: Train the NMT architecture.
  • Decoding/Testing: Realize the beam search to translate sentences from German to English.

Evaluation

Perplexity and BLEU scores on validation/test sets.

Papers

BLEU calculation

We used for the BLEU calculation the multi_bleu.pl script from the moses project: https://github.com/moses-smt/mosesdecoder/blob/master/scripts/generic/multi-bleu.perl

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