SAN_D2T

Generate text from Structured-data (i.e. Wikipedia Table).

Dependencies

• PyTorch - Models, computational graphs are built with PyTorch.
• Numpy - Numpy provides the most-frequently-used operations for tensors.
• Matplotlib - Matplotlib provides toolkits for visualizations in Python.
• NLTK - Natural Language Toolkit, BLEU-Score calculator needed.
• pyrouge - A Python wrapper for the ROUGE evaluation package.
• tqdm - Make epoch loops show a progress meter.

Instructions

Prepare Data

Download dataset: WikiBio (Wikipedia biography dataset) released by David Grangier. It consists of the first paragraph and the infobox.

Decompressing the zip files and copy into a folder named 'data/original/'.

The cleaned data we have preprocessed can be downloaded at Google Drive .

Usage

Run python preprocess/preprocess.py to process original files into json-format files into 'data/' folder.

Run python train.py to continue training/save model, and evaluate the pre-trained models with metrics BLEU and ROUGE.

The model files we have trained can be downloaded at Google Drive .

Run python data2text.py to generate utterances and attention maps.