Research Advances In Semantic Slot Filling
This repo mainly summary latest research advances on semantic slot filling.
Note: these results from ATIS dataset.
|Model||F1 Score||Intent Accuracy||Year|
|Recursive NN||0.9396||0.954||Guo et al. 2014|
|Joint model with recurrent intent and slot label context||0.9447||0.984||Liu and Lane, 2016b|
|Joint model with recurrent slot label context||0.9464||0.984||Liu and Lane, 2016b|
|RNN with Label Sampling||0.9489||NA||Liu and Lane, 2015|
|Hybrid RNN||0.9506||NA||Mesnil et al., 2015|
|RNN-EM||0.9525||NA||Peng and Yao, 2015|
|CNN-CRF||0.9435||NA||Xu and Sarikaya, 2013|
|Encoder-labeler Deep LSTM||0.9566||NA||Kurata et al., 2016|
|Joint GRU model(W)||0.9549||0.9810||Zhang and Wang, 2016|
|Attention Encoder-Decoder NN||0.9587||0.9843||Liu and Lane, 2016a|
|Bi-model without a decoder||0.9665||0.9876||Wang and Shen, 2018|
|Bi-model with a decoder||0.9689||0.9899||Wang and Shen, 2018|
- Tur, Gokhan, Dilek Hakkani-Tür, and Larry Heck. "What is left to be understood in ATIS?." Spoken Language Technology Workshop (SLT), 2010 IEEE. IEEE, 2010.
- Yao, Kaisheng, et al. "Spoken language understanding using long short-term memory neural networks." Spoken Language Technology Workshop (SLT), 2014 IEEE. IEEE, 2014.
Vu, Ngoc Thang, et al. "Bi-directional recurrent neural network with ranking loss for spoken language understanding." Acoustics, Speech and Signal Processing (ICASSP), 2016 IEEE International Conference on. Ieee, 2016.
Zhu, Su, and Kai Yu. "Encoder-decoder with focus-mechanism for sequence labelling based spoken language understanding." 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2017.
Wang, Yu, Yilin Shen, and Hongxia Jin. "A Bi-model based RNN Semantic Frame Parsing Model for Intent Detection and Slot Filling." Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers). Vol. 2. 2018.