Discovering Dialogue Slots with Weak Supervision

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F21%3A10440539" target="_blank" >RIV/00216208:11320/21:10440539 - isvavai.cz</a>

Result on the web

<a href="https://aclanthology.org/2021.acl-long.189" target="_blank" >https://aclanthology.org/2021.acl-long.189</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.18653/v1/2021.acl-long.189" target="_blank" >10.18653/v1/2021.acl-long.189</a>

Result language

angličtina

Original language name

Discovering Dialogue Slots with Weak Supervision

Original language description

Task-oriented dialogue systems typically require manual annotation of dialogue slots in training data, which is costly to obtain. We propose a method that eliminates this requirement: We use weak supervision from existing linguistic annotation models to identify potential slot candidates, then automatically identify domain-relevant slots by using clustering algorithms. Furthermore, we use the resulting slot annotation to train a neural-network-based tagger that is able to perform slot tagging with no human intervention. This tagger is trained solely on the outputs of our method and thus does not rely on any labeled data. Our model demonstrates state-of-the-art performance in slot tagging without labeled training data on four different dialogue domains. Moreover, we find that slot annotations discovered by our model significantly improve the performance of an end-to-end dialogue response generation model, compared to using no slot annotation at all.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2021

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing

ISBN

978-1-954085-52-7

ISSN

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e-ISSN

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Number of pages

13

Pages from-to

2430-2442

Publisher name

Association for Computational Linguistics

Place of publication

Stroudsburg, PA, USA

Event location

Online

Event date

Aug 2, 2021

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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