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The SpeDial datasets: datasets for Spoken Dialogue Systems analytics
KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH.ORCID iD: 0000-0002-8773-9216
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2016 (English)In: LREC 2016, Tenth International Conference on Language Resources and Evaluation, 2016Conference paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
2016.
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:kth:diva-204005OAI: oai:DiVA.org:kth-204005DiVA: diva2:1083721
Conference
10th edition of the Language Resources and Evaluation Conference
Note

QC 20170411

Available from: 2017-03-22 Created: 2017-03-22 Last updated: 2017-04-11Bibliographically approved

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