Predicting depression and emotions in the cross-roads of cultures, para-linguistics, and non-linguistics
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Dosyalar
Tarih
2019
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Association for Computing Machinery, Inc
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Cross-language, cross-cultural emotion recognition and accurate prediction of affective disorders are two of the major challenges in affective computing today. In this work, we compare several systems for Detecting Depression with AI Sub-challenge (DDS) and Cross-cultural Emotion Sub-challenge (CES) that are published as part of the Audio-Visual Emotion Challenge (AVEC) 2019. For both sub-challenges, we benefit from the baselines, while introducing our own features and regression models. For the DDS challenge, where ASR transcripts are provided by the organizers, we propose simple linguistic and word-duration features. These ASR transcriptbased features are shown to outperform the state of the art audio visual features for this task, reaching a test set Concordance Correlation Coefficient (CCC) performance of 0.344 in comparison to a challenge baseline of 0.120. Our results show that non-verbal parts of the signal are important for detection of depression, and combining this with linguistic information produces the best results. For CES, the proposed systems using unsupervised feature adaptation outperform the challenge baselines on emotional primitives, reaching test set CCC performances of 0.466 and 0.499 for arousal and valence, respectively. © 2019 Association for Computing Machinery.
Açıklama
ACM SIGMM
9th International Audio/Visual Emotion Challenge and Workshop, AVEC 2019, held in conjunction with the ACM Multimedia 2019 -- 21 October 2019 -- -- 153196
9th International Audio/Visual Emotion Challenge and Workshop, AVEC 2019, held in conjunction with the ACM Multimedia 2019 -- 21 October 2019 -- -- 153196
Anahtar Kelimeler
Affective Computing, Cross-Cultural Emotion Recognition, Depression Severity Prediction, PTSD, Audio systems, Forecasting, Regression analysis, Speech recognition, Accurate prediction, Affective Computing, Audio-visual features, Correlation coefficient, Emotion recognition, Feature adaptation, Linguistic information, PTSD, Linguistics
Kaynak
AVEC 2019 - Proceedings of the 9th International Audio/Visual Emotion Challenge and Workshop, co-located with MM 2019
