Improving Dialogue Smoothing with A-priori State Pruning

Manex Serras; María Inés Torres; Arantza Del Pozo

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Paper

Improving Dialogue Smoothing with A-priori State Pruning

Topics: Bayesian Models and Stochastic Methods; Classification and Clustering; Natural Language Processing; Virtual Environments

In Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods ICPRAM - Volume 1, 607-614, 2020 , Valletta, Malta

Authors: Manex Serras ¹ ; María Inés Torres ² and Arantza Del Pozo ¹

Affiliations: ¹ Speech and Natural Language Technologies, Vicomtech, Paseo Mikeletegi 57, Donostia-San Sebastian, Spain ; ² Speech Interactive Research Group, Universidad del País Vasco UPV/EHU, Campus of Leioa, Leioa, Spain

Keyword(s): Dialogue State Pruning, Dialogue Breakdown, Attributed Probabilistic Finite State Bi-Automata, Dialogue Systems.

Abstract: When Dialogue Systems (DS) face real usage, a challenge to solve is managing unforeseen situations without breaking the coherence of the dialogue. One way to achieve this is by redirecting the interaction to known dialogue states in a transparent way. This work proposes a simple a-priori pruning method to rule out invalid candidates when searching for similar dialogue states in unexpected scenarios. The proposed method is evaluated on a User Model (UM) based on Attributed Probabilistic Finite State Bi-Automata (A-PFSBA), trained on the Dialogue State Tracking Challenge 2 (DSTC2) corpus. Results show that the proposed technique improves response times and achieves higher F1 scores than previous A-PFSBA implementations and deep learning models.

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Paper citation in several formats:

Serras, M.; Torres, M. and Pozo, A. (2020). Improving Dialogue Smoothing with A-priori State Pruning. In Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-397-1; ISSN 2184-4313, SciTePress, pages 607-614. DOI: 10.5220/0009184206070614

@conference{icpram20,
author={Manex Serras. and María Inés Torres. and Arantza Del Pozo.},
title={Improving Dialogue Smoothing with A-priori State Pruning},
booktitle={Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2020},
pages={607-614},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009184206070614},
isbn={978-989-758-397-1},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Improving Dialogue Smoothing with A-priori State Pruning
SN - 978-989-758-397-1
IS - 2184-4313
AU - Serras, M.
AU - Torres, M.
AU - Pozo, A.
PY - 2020
SP - 607
EP - 614
DO - 10.5220/0009184206070614
PB - SciTePress