Yun-Nung (Vivian) Chen, y.v.chen@ieee.org
This model learns various RNN models (RNN, GRU, LSTM, etc.) for joint semantic parsing. The intent and slots are tagged in a single network model.
- Python
- Numpy
- Scipy
- Keras
- H5py
- Train: word sequences with IOB slot tags and the intent label (data/atis.train.w-intent.iob)
- Test: word sequences with IOB slot tags and the intent label (data/atis.test.w-intent.iob)
Main papers to be cited
@Inproceedings{hakkani-tur2016multi,
author = {Hakkani-Tur, Dilek and Tur, Gokhan and Celikyilmaz, Asli and Chen, Yun-Nung and Gao, Jianfeng and Wang, Ye-Yi},
title = {Multi-Domain Joint Semantic Frame Parsing using Bi-directional RNN-LSTM},
booktitle = {Proceedings of Interspeech},
year = {2016}
}