liebkne/pruned-nlu

Code for the paper "Accelerating Natural Language Understanding in Task-Oriented Dialog"

Accelerating NLU in Task-Oriented Dialog

Code for ACL ConvAI workshop paper "Accelerating Natural Language Understanding in Task-Oriented Dialog".

Requirements

• >= Python 3.7
• >= PyTorch 1.4.0
• seqeval

Setup

Download GloVe embeddings:

wget http://nlp.stanford.edu/data/glove.6B.zip
unzip glove.6B.zip -d glove

Files

• train.py, test.py, distill.py, timer.py, prune.py: runnable scripts, check each file's argparse for options and details
• models.py: intent detection, slot-filling, and multi-task (joint intent detection and slot filling) CNN models
• dataset.py: dataset loading abstractions
• util.py: common code
• models/: pretrained models, 5 duplicates of each
• datasets/: prepared ATIS and Snips datasets

Citation

@inproceedings{ahuja-desai-2020-accelerating,
    title = "Accelerating Natural Language Understanding in Task-Oriented Dialog",
    author = "Ahuja, Ojas  and
      Desai, Shrey",
    booktitle = "Proceedings of the 2nd Workshop on Natural Language Processing for Conversational AI",
    year = "2020",
    publisher = "Association for Computational Linguistics"
}

Contact

[email protected]