@inproceedings{ultes-etal-2018-addressing,
title = "Addressing Objects and Their Relations: The Conversational Entity Dialogue Model",
author = "Ultes, Stefan and
Budzianowski, Pawe{\l} and
Casanueva, I{\~n}igo and
Rojas-Barahona, Lina M. and
Tseng, Bo-Hsiang and
Wu, Yen-Chen and
Young, Steve and
Ga{\v{s}}i{\'c}, Milica",
editor = "Komatani, Kazunori and
Litman, Diane and
Yu, Kai and
Papangelis, Alex and
Cavedon, Lawrence and
Nakano, Mikio",
booktitle = "Proceedings of the 19th Annual {SIG}dial Meeting on Discourse and Dialogue",
month = jul,
year = "2018",
address = "Melbourne, Australia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W18-5032",
doi = "10.18653/v1/W18-5032",
pages = "273--283",
abstract = "Statistical spoken dialogue systems usually rely on a single- or multi-domain dialogue model that is restricted in its capabilities of modelling complex dialogue structures, e.g., relations. In this work, we propose a novel dialogue model that is centred around entities and is able to model relations as well as multiple entities of the same type. We demonstrate in a prototype implementation benefits of relation modelling on the dialogue level and show that a trained policy using these relations outperforms the multi-domain baseline. Furthermore, we show that by modelling the relations on the dialogue level, the system is capable of processing relations present in the user input and even learns to address them in the system response.",
}
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<abstract>Statistical spoken dialogue systems usually rely on a single- or multi-domain dialogue model that is restricted in its capabilities of modelling complex dialogue structures, e.g., relations. In this work, we propose a novel dialogue model that is centred around entities and is able to model relations as well as multiple entities of the same type. We demonstrate in a prototype implementation benefits of relation modelling on the dialogue level and show that a trained policy using these relations outperforms the multi-domain baseline. Furthermore, we show that by modelling the relations on the dialogue level, the system is capable of processing relations present in the user input and even learns to address them in the system response.</abstract>
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%0 Conference Proceedings
%T Addressing Objects and Their Relations: The Conversational Entity Dialogue Model
%A Ultes, Stefan
%A Budzianowski, Paweł
%A Casanueva, Iñigo
%A Rojas-Barahona, Lina M.
%A Tseng, Bo-Hsiang
%A Wu, Yen-Chen
%A Young, Steve
%A Gašić, Milica
%Y Komatani, Kazunori
%Y Litman, Diane
%Y Yu, Kai
%Y Papangelis, Alex
%Y Cavedon, Lawrence
%Y Nakano, Mikio
%S Proceedings of the 19th Annual SIGdial Meeting on Discourse and Dialogue
%D 2018
%8 July
%I Association for Computational Linguistics
%C Melbourne, Australia
%F ultes-etal-2018-addressing
%X Statistical spoken dialogue systems usually rely on a single- or multi-domain dialogue model that is restricted in its capabilities of modelling complex dialogue structures, e.g., relations. In this work, we propose a novel dialogue model that is centred around entities and is able to model relations as well as multiple entities of the same type. We demonstrate in a prototype implementation benefits of relation modelling on the dialogue level and show that a trained policy using these relations outperforms the multi-domain baseline. Furthermore, we show that by modelling the relations on the dialogue level, the system is capable of processing relations present in the user input and even learns to address them in the system response.
%R 10.18653/v1/W18-5032
%U https://aclanthology.org/W18-5032
%U https://doi.org/10.18653/v1/W18-5032
%P 273-283
Markdown (Informal)
[Addressing Objects and Their Relations: The Conversational Entity Dialogue Model](https://aclanthology.org/W18-5032) (Ultes et al., SIGDIAL 2018)
ACL
- Stefan Ultes, Paweł Budzianowski, Iñigo Casanueva, Lina M. Rojas-Barahona, Bo-Hsiang Tseng, Yen-Chen Wu, Steve Young, and Milica Gašić. 2018. Addressing Objects and Their Relations: The Conversational Entity Dialogue Model. In Proceedings of the 19th Annual SIGdial Meeting on Discourse and Dialogue, pages 273–283, Melbourne, Australia. Association for Computational Linguistics.