A Unifying View On Task-oriented Dialogue Annotation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F22%3A10457001" target="_blank" >RIV/00216208:11320/22:10457001 - isvavai.cz</a>
Result on the web
<a href="https://aclanthology.org/2022.lrec-1.137/" target="_blank" >https://aclanthology.org/2022.lrec-1.137/</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
A Unifying View On Task-oriented Dialogue Annotation
Original language description
Every model is only as strong as the data that it is trained on. In this paper, we present a new dataset, obtained by merging four publicly available annotated corpora for task-oriented dialogues in several domains (MultiWOZ 2.2, CamRest676, DSTC2 and Schema-Guided Dialogue Dataset). This way, we assess the feasibility of providing a unified ontology and annotation schema covering several domains with a relatively limited effort. We analyze the characteristics of the resulting dataset along three main dimensions: language, information content and performance. We focus on aspects likely to be pertinent for improving dialogue success, e.g. dialogue consistency. Furthermore, to assess the usability of this new corpus, we thoroughly evaluate dialogue generation performance under various conditions with the help of two prominent recent end-to-end dialogue models: MarCo and GPT-2. These models were selected as popular open implementations representative of the two main dimensions of dialogue modelling. Whil
Czech name
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Czech description
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Classification
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)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022)
ISBN
979-10-95546-72-6
ISSN
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e-ISSN
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Number of pages
11
Pages from-to
1286-1296
Publisher name
European Language Resources Association
Place of publication
Marseille, France
Event location
Marseille, France
Event date
Jun 20, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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