Towards a Better Gold Standard: Denoising and Modelling Continuous Emotion Annotations Based on Feature Agglomeration and Outlier Regularisation

Wang, Chen; Lopes, Phil; Pun, Thierry; Chanel, Guillaume

doi:10.1145/3266302.3266307

Proceedings chapter

English

Towards a Better Gold Standard: Denoising and Modelling Continuous Emotion Annotations Based on Feature Agglomeration and Outlier Regularisation

ContributorsWang, Chen; Lopes, Phil; Pun, Thierry; Chanel, Guillaume

Presented atSeoul (Republic of Korea), October 22, 2018

Published inAVEC'18 Proceedings of the 2018 on Audio/Visual Emotion Challenge and Workshop, p. 73-81

PublisherACM Press

Publication date2018

Affiliation entities

Research groups

Citation (ISO format)

WANG, Chen et al. Towards a Better Gold Standard: Denoising and Modelling Continuous Emotion Annotations Based on Feature Agglomeration and Outlier Regularisation. In: AVEC′18 Proceedings of the 2018 on Audio/Visual Emotion Challenge and Workshop. Seoul (Republic of Korea). [s.l.] : ACM Press, 2018. p. 73–81. doi: 10.1145/3266302.3266307

Proceedings chapter (Published version)

Identifiers

PID : unige:111398
DOI : 10.1145/3266302.3266307

Additional URL for this publicationhttp://dl.acm.org/citation.cfm?doid=3266302.3266307

ISBN978-1-4503-5983-2

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Towards a Better Gold Standard: Denoising and Modelling Continuous Emotion Annotations Based on Feature Agglomeration and Outlier Regularisation

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