@inproceedings{henderson-etal-2019-polyresponse,
title = "{P}oly{R}esponse: A Rank-based Approach to Task-Oriented Dialogue with Application in Restaurant Search and Booking",
author = "Henderson, Matthew and
Vuli{\'c}, Ivan and
Casanueva, I{\~n}igo and
Budzianowski, Pawe{\l} and
Gerz, Daniela and
Coope, Sam and
Spithourakis, Georgios and
Wen, Tsung-Hsien and
Mrk{\v{s}}i{\'c}, Nikola and
Su, Pei-Hao",
editor = "Pad{\'o}, Sebastian and
Huang, Ruihong",
booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations",
month = nov,
year = "2019",
address = "Hong Kong, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D19-3031",
doi = "10.18653/v1/D19-3031",
pages = "181--186",
abstract = "We present PolyResponse, a conversational search engine that supports task-oriented dialogue. It is a retrieval-based approach that bypasses the complex multi-component design of traditional task-oriented dialogue systems and the use of explicit semantics in the form of task-specific ontologies. The PolyResponse engine is trained on hundreds of millions of examples extracted from real conversations: it learns what responses are appropriate in different conversational contexts. It then ranks a large index of text and visual responses according to their similarity to the given context, and narrows down the list of relevant entities during the multi-turn conversation. We introduce a restaurant search and booking system powered by the PolyResponse engine, currently available in 8 different languages.",
}
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%0 Conference Proceedings
%T PolyResponse: A Rank-based Approach to Task-Oriented Dialogue with Application in Restaurant Search and Booking
%A Henderson, Matthew
%A Vulić, Ivan
%A Casanueva, Iñigo
%A Budzianowski, Paweł
%A Gerz, Daniela
%A Coope, Sam
%A Spithourakis, Georgios
%A Wen, Tsung-Hsien
%A Mrkšić, Nikola
%A Su, Pei-Hao
%Y Padó, Sebastian
%Y Huang, Ruihong
%S Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations
%D 2019
%8 November
%I Association for Computational Linguistics
%C Hong Kong, China
%F henderson-etal-2019-polyresponse
%X We present PolyResponse, a conversational search engine that supports task-oriented dialogue. It is a retrieval-based approach that bypasses the complex multi-component design of traditional task-oriented dialogue systems and the use of explicit semantics in the form of task-specific ontologies. The PolyResponse engine is trained on hundreds of millions of examples extracted from real conversations: it learns what responses are appropriate in different conversational contexts. It then ranks a large index of text and visual responses according to their similarity to the given context, and narrows down the list of relevant entities during the multi-turn conversation. We introduce a restaurant search and booking system powered by the PolyResponse engine, currently available in 8 different languages.
%R 10.18653/v1/D19-3031
%U https://aclanthology.org/D19-3031
%U https://doi.org/10.18653/v1/D19-3031
%P 181-186
Markdown (Informal)
[PolyResponse: A Rank-based Approach to Task-Oriented Dialogue with Application in Restaurant Search and Booking](https://aclanthology.org/D19-3031) (Henderson et al., EMNLP-IJCNLP 2019)
ACL
- Matthew Henderson, Ivan Vulić, Iñigo Casanueva, Paweł Budzianowski, Daniela Gerz, Sam Coope, Georgios Spithourakis, Tsung-Hsien Wen, Nikola Mrkšić, and Pei-Hao Su. 2019. PolyResponse: A Rank-based Approach to Task-Oriented Dialogue with Application in Restaurant Search and Booking. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations, pages 181–186, Hong Kong, China. Association for Computational Linguistics.