@inproceedings{gosko-etal-2021-domain,
title = "Domain Expert Platform for Goal-Oriented Dialog Collection",
author = "Go{\v{s}}ko, Didzis and
Znotins, Arturs and
Skadina, Inguna and
Gruzitis, Normunds and
Ne{\v{s}}pore-B{\=e}rzkalne, Gunta",
editor = "Gkatzia, Dimitra and
Seddah, Djam{\'e}",
booktitle = "Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations",
month = apr,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.eacl-demos.35",
doi = "10.18653/v1/2021.eacl-demos.35",
pages = "295--301",
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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T Domain Expert Platform for Goal-Oriented Dialog Collection
%A Goško, Didzis
%A Znotins, Arturs
%A Skadina, Inguna
%A Gruzitis, Normunds
%A Nešpore-Bērzkalne, Gunta
%Y Gkatzia, Dimitra
%Y Seddah, Djamé
%S Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations
%D 2021
%8 April
%I Association for Computational Linguistics
%C Online
%F gosko-etal-2021-domain
%X 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.
%R 10.18653/v1/2021.eacl-demos.35
%U https://aclanthology.org/2021.eacl-demos.35
%U https://doi.org/10.18653/v1/2021.eacl-demos.35
%P 295-301
Markdown (Informal)
[Domain Expert Platform for Goal-Oriented Dialog Collection](https://aclanthology.org/2021.eacl-demos.35) (Goško et al., EACL 2021)
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.