Code for "Jhamtani H., Gangal V., Hovy E. and Nyberg E. Shakespearizing Modern Language Using Copy-Enriched Sequence to Sequence Models" Workshop on Stylistic Variation, EMNLP 2017

Code has been tested with Tensorflow version 1.1.0

• If you use this code or the processed data, please consider citing Jhamtani H., Gangal V., Hovy E. and Nyberg E. Shakespearizing Modern Language Using Copy-Enriched Sequence to Sequence Models" Workshop on Stylistic Variation, EMNLP 2017
• If you use the data, please consder citing "Wei Xu, Alan Ritter, William B Dolan, Ralph Grish- man, and Colin Cherry. 2012. Paraphrasing for style. In 24th International Conference on Computational Linguistics, COLING 2012."

Instructions to run:
Preprocessing:

• Change working directory to code/main/
• Create a new directory named 'tmp'
• python mt_main.py preprocessing
  

Pointer model:

• First run pre-processing
• Change working directory to code/main/
• python mt_main.py train 10 pointer_model
  For inference:
  
• Change working directory to code/main/
• python mt_main.py inference tmp/pointer_model7.ckpt greedy
  

Normal seq2seq model:

• First run pre-processing
• Change working directory to code/main/
• python mt_main.py train 10 seq2seq
  For inference:
  
• Change working directory to code/main/
• python mt_main.py inference tmp/seq2seq5.ckpt greedy
  

Post-Processing: There are two post-processing actions which one may be interested in performing:

1. Visualizing attention matrices
2. Replacing UNKS in hypothesis with their highest-aligned (attention) input tokens. For both of these actions, refer to the running instructions in code/main/post_process.py (comments commencing the file). The file can be run in two modes, to perform 1 (write) and 2 (postProcess) respectively*. *Not elaborated on here to preserve conciseness and clarity.

Baseline (Dictionary):

• Change working directory to code/baselines/
• python dictionary_baseline.py ../../data/shakespeare.dict ../../data/test.modern.nltktok ../../data/test.dictBaseline
• The test.dictBaseline file contains the output (Shakespearean) of the dictionary baseline.
• To evaluate BLEU:
  • Change working directory to code/main/
  • perl multi-bleu.perl -lc ../../data/test.original.nltktok < ../../data/test.dictBaseline

Baseline (statistical MT)

• Please follow instructions in "Wei Xu, Alan Ritter, William B Dolan, Ralph Grish- man, and Colin Cherry. 2012. Paraphrasing for style. In 24th International Conference on Computational Linguistics, COLING 2012."