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Tensorflow 2.0 implementation of automatic punctuation with RNN + attention

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Tensorflow 2.0 implementation of RNN + attention-based automatic punctuation

Derived from this project written in Theano.

At this stage this is a rough draft, tested only with a single type of "punctuation" (actually, sentence boundaries). However, it is easily adapted to any number of punctuation markers.

Also added a little script to infer and visualize the attention weights for any sentence fed to a trained model.

Hyperparameters and paths to data and checkpoints are written in a bash file to be sourced before running the script, e.g.

source env.sh
python 01_train.python

See example_data to see how the data should be formatted.

Preprocessing scripts are not provided in this version.

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