@inproceedings{lopes-etal-2016-spedial,
title = "The {S}pe{D}ial datasets: datasets for Spoken Dialogue Systems analytics",
author = "Lopes, Jos{\'e} and
Chorianopoulou, Arodami and
Palogiannidi, Elisavet and
Moniz, Helena and
Abad, Alberto and
Louka, Katerina and
Iosif, Elias and
Potamianos, Alexandros",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Declerck, Thierry and
Goggi, Sara and
Grobelnik, Marko and
Maegaard, Bente and
Mariani, Joseph and
Mazo, Helene and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Tenth International Conference on Language Resources and Evaluation ({LREC}'16)",
month = may,
year = "2016",
address = "Portoro{\v{z}}, Slovenia",
publisher = "European Language Resources Association (ELRA)",
url = "https://aclanthology.org/L16-1016",
pages = "104--110",
abstract = "The SpeDial consortium is sharing two datasets that were used during the SpeDial project. By sharing them with the community we are providing a resource to reduce the duration of cycle of development of new Spoken Dialogue Systems (SDSs). The datasets include audios and several manual annotations, i.e., miscommunication, anger, satisfaction, repetition, gender and task success. The datasets were created with data from real users and cover two different languages: English and Greek. Detectors for miscommunication, anger and gender were trained for both systems. The detectors were particularly accurate in tasks where humans have high annotator agreement such as miscommunication and gender. As expected due to the subjectivity of the task, the anger detector had a less satisfactory performance. Nevertheless, we proved that the automatic detection of situations that can lead to problems in SDSs is possible and can be a promising direction to reduce the duration of SDS{'}s development cycle.",
}
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%0 Conference Proceedings
%T The SpeDial datasets: datasets for Spoken Dialogue Systems analytics
%A Lopes, José
%A Chorianopoulou, Arodami
%A Palogiannidi, Elisavet
%A Moniz, Helena
%A Abad, Alberto
%A Louka, Katerina
%A Iosif, Elias
%A Potamianos, Alexandros
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Goggi, Sara
%Y Grobelnik, Marko
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Mazo, Helene
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16)
%D 2016
%8 May
%I European Language Resources Association (ELRA)
%C Portorož, Slovenia
%F lopes-etal-2016-spedial
%X The SpeDial consortium is sharing two datasets that were used during the SpeDial project. By sharing them with the community we are providing a resource to reduce the duration of cycle of development of new Spoken Dialogue Systems (SDSs). The datasets include audios and several manual annotations, i.e., miscommunication, anger, satisfaction, repetition, gender and task success. The datasets were created with data from real users and cover two different languages: English and Greek. Detectors for miscommunication, anger and gender were trained for both systems. The detectors were particularly accurate in tasks where humans have high annotator agreement such as miscommunication and gender. As expected due to the subjectivity of the task, the anger detector had a less satisfactory performance. Nevertheless, we proved that the automatic detection of situations that can lead to problems in SDSs is possible and can be a promising direction to reduce the duration of SDS’s development cycle.
%U https://aclanthology.org/L16-1016
%P 104-110
Markdown (Informal)
[The SpeDial datasets: datasets for Spoken Dialogue Systems analytics](https://aclanthology.org/L16-1016) (Lopes et al., LREC 2016)
ACL
- José Lopes, Arodami Chorianopoulou, Elisavet Palogiannidi, Helena Moniz, Alberto Abad, Katerina Louka, Elias Iosif, and Alexandros Potamianos. 2016. The SpeDial datasets: datasets for Spoken Dialogue Systems analytics. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 104–110, Portorož, Slovenia. European Language Resources Association (ELRA).