TY - GEN
T1 - Deep Learning for Dialogue Systems
AU - Chen, Yun Nung
AU - Celikyilmaz, Asli
AU - Hakkani-Tür, Dilek
N1 - Publisher Copyright:
© 2018 COLING 2018 - 27th International Conference on Computational Linguistics, Proceedings of Tutorial Abstracts. All rights reserved.
PY - 2018
Y1 - 2018
N2 - Goal-oriented spoken dialogue systems have been the most prominent component in todays virtual personal assistants, which allow users to speak naturally in order to finish tasks more efficiently. The advancement of deep learning technologies has recently risen the applications of neural models to dialogue modeling. However, applying deep learning technologies for building robust and scalable dialogue systems is still a challenging task and an open research area as it requires deeper understanding of the classic pipelines as well as detailed knowledge of the prior work and the recent state-of-the-art work. Therefore, this tutorial is designed to focus on an overview of dialogue system development while describing most recent research for building dialogue systems, and summarizing the challenges, in order to allow researchers to study the potential improvements of the state-of-the-art dialogue systems. The tutorial material is available at http://deepdialogue.miulab.tw.
AB - Goal-oriented spoken dialogue systems have been the most prominent component in todays virtual personal assistants, which allow users to speak naturally in order to finish tasks more efficiently. The advancement of deep learning technologies has recently risen the applications of neural models to dialogue modeling. However, applying deep learning technologies for building robust and scalable dialogue systems is still a challenging task and an open research area as it requires deeper understanding of the classic pipelines as well as detailed knowledge of the prior work and the recent state-of-the-art work. Therefore, this tutorial is designed to focus on an overview of dialogue system development while describing most recent research for building dialogue systems, and summarizing the challenges, in order to allow researchers to study the potential improvements of the state-of-the-art dialogue systems. The tutorial material is available at http://deepdialogue.miulab.tw.
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M3 - Conference contribution
AN - SCOPUS:85078817398
T3 - COLING 2018 - 27th International Conference on Computational Linguistics, Proceedings of Tutorial Abstracts
SP - 25
EP - 31
BT - COLING 2018 - 27th International Conference on Computational Linguistics, Proceedings of Tutorial Abstracts
PB - Association for Computational Linguistics (ACL)
T2 - 27th International Conference on Computational Linguistics, COLING 2018
Y2 - 20 August 2018 through 26 August 2018
ER -