NDLI: Affect burst detection using multi-modal cues

Content Provider	IEEE Xplore Digital Library
Author	Turker, B.B. Marzban, S. Tevfik Sezgin, M. Yemez, Y. Erzin, E.
Copyright Year	2015
Description	Author affiliation: Bilgisayar Muhendisligi Bolumu, Koc Univ., İstanbul, Turkey (Marzban, S.; Tevfik Sezgin, M.; Yemez, Y.) \|\| Elektrik ve Elektron. Muhendisligi Bolumu, Koc Univ., İstanbul, Turkey (Turker, B.B.; Erzin, E.)
Abstract	Recently, affect bursts have gained significant importance in the field of emotion recognition since they can serve as prior in recognising underlying affect bursts. In this paper we propose a data driven approach for detecting affect bursts using multimodal streams of input such as audio and facial landmark points. The proposed Gaussian Mixture Model based method learns each modality independently followed by combining the probabilistic outputs to form a decision. This gives us an edge over feature fusion based methods as it allows us to handle events when one of the modalities is too noisy or not available. We demonstrate robustness of the proposed approach on 'Interactive emotional dyadic motion capture database' (IEMOCAP) which contains realistic and natural dyadic conversations. This database is annotated by three annotators to segment and label affect bursts to be used for training and testing purposes. We also present performance comparison between SVM based methods and GMM based methods for the same configuration of experiments.
Starting Page	1006
Ending Page	1009
File Size	135319
Page Count	4
File Format	PDF
ISBN	9781467373869
DOI	10.1109/SIU.2015.7130002
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-05-16
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Emotion recognition Affective computing Affective Computing and Interaction Databases Computational modeling Hidden Markov models Artificial neural networks Applied Machine Learning Speech Affect Burst Detection
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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