Domain Expert Platform for Goal-Oriented Dialog Collection

Didzis Goško, Arturs Znotins, Inguna Skadina, Normunds Gruzitis, Gunta Nešpore-Bērzkalne

Abstract
Today, most dialogue systems are fully or partly built using neural network architectures. A crucial prerequisite for the creation of a goal-oriented neural network dialogue system is a dataset that represents typical dialogue scenarios and includes various semantic annotations, e.g. intents, slots and dialogue actions, that are necessary for training a particular neural network architecture. In this demonstration paper, we present an easy to use interface and its back-end which is oriented to domain experts for the collection of goal-oriented dialogue samples. The platform not only allows to collect or write sample dialogues in a structured way, but also provides a means for simple annotation and interpretation of the dialogues. The platform itself is language-independent; it depends only on the availability of particular language processing components for a specific language. It is currently being used to collect dialogue samples in Latvian (a highly inflected language) which represent typical communication between students and the student service.
Anthology ID:
2021.eacl-demos.35
Volume:
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations
Month:
April
Year:
2021
Address:
Online
Venue:
EACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
295–301
Language:
URL:
https://aclanthology.org/2021.eacl-demos.35
DOI:
10.18653/v1/2021.eacl-demos.35
Bibkey:
Cite (ACL):
Didzis Goško, Arturs Znotins, Inguna Skadina, Normunds Gruzitis, and Gunta Nešpore-Bērzkalne. 2021. Domain Expert Platform for Goal-Oriented Dialog Collection. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations, pages 295–301, Online. Association for Computational Linguistics.
Cite (Informal):
Domain Expert Platform for Goal-Oriented Dialog Collection (Goško et al., EACL 2021)
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PDF:
https://preview.aclanthology.org/ingestion-script-update/2021.eacl-demos.35.pdf
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