Arodami Chorianopoulou


2016

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The SpeDial datasets: datasets for Spoken Dialogue Systems analytics
José Lopes | Arodami Chorianopoulou | Elisavet Palogiannidi | Helena Moniz | Alberto Abad | Katerina Louka | Elias Iosif | Alexandros Potamianos
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

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.

2014

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tucSage: Grammar Rule Induction for Spoken Dialogue Systems via Probabilistic Candidate Selection
Arodami Chorianopoulou | Georgia Athanasopoulou | Elias Iosif | Ioannis Klasinas | Alexandros Potamianos
Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014)