Hiroshi Tsukahara


2021

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Integrated taxonomy of errors in chat-oriented dialogue systems
Ryuichiro Higashinaka | Masahiro Araki | Hiroshi Tsukahara | Masahiro Mizukami
Proceedings of the 22nd Annual Meeting of the Special Interest Group on Discourse and Dialogue

This paper proposes a taxonomy of errors in chat-oriented dialogue systems. Previously, two taxonomies were proposed; one is theory-driven and the other data-driven. The former suffers from the fact that dialogue theories for human conversation are often not appropriate for categorizing errors made by chat-oriented dialogue systems. The latter has limitations in that it can only cope with errors of systems for which we have data. This paper integrates these two taxonomies to create a comprehensive taxonomy of errors in chat-oriented dialogue systems. We found that, with our integrated taxonomy, errors can be reliably annotated with a higher Fleiss’ kappa compared with the previously proposed taxonomies.

2015

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Towards Taxonomy of Errors in Chat-oriented Dialogue Systems
Ryuichiro Higashinaka | Kotaro Funakoshi | Masahiro Araki | Hiroshi Tsukahara | Yuka Kobayashi | Masahiro Mizukami
Proceedings of the 16th Annual Meeting of the Special Interest Group on Discourse and Dialogue

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Inducing Word and Part-of-Speech with Pitman-Yor Hidden Semi-Markov Models
Kei Uchiumi | Hiroshi Tsukahara | Daichi Mochihashi
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

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System Utterance Generation by Label Propagation over Association Graph of Words and Utterance Patterns for Open-Domain Dialogue Systems
Hiroshi Tsukahara | Kei Uchiumi
Proceedings of the 29th Pacific Asia Conference on Language, Information and Computation

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Fatal or not? Finding errors that lead to dialogue breakdowns in chat-oriented dialogue systems
Ryuichiro Higashinaka | Masahiro Mizukami | Kotaro Funakoshi | Masahiro Araki | Hiroshi Tsukahara | Yuka Kobayashi
Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing