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Interpersonal Synchrony: From Social Perception to Social Interaction
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In: Social Signal Processing ; https://hal-pasteur.archives-ouvertes.fr/pasteur-02070422 ; Edited by Judee K. Burgoon, University of Arizona Nadia Magnenat-Thalmann, Université de Genève Maja Pantic, Imperial College London Alessandro Vinciarelli, University of Glasgow. Social Signal Processing, Cambridge University Press, pp.202-212, 2017, Social Signal Processing, 9781316676202. ⟨10.1017/9781316676202.015⟩ ; https://www.cambridge.org/core/books/social-signal-processing/interpersonal-synchrony-from-social-perception-to-social-interaction/50D491B6C3AB7767858C80CF612C28A5 (2017)
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Fera 2015 - second facial expression recognition and analysis challenge
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In: http://www.cs.nott.ac.uk/%7Epszmv/Documents/FERA2015.pdf (2015)
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M.: A semi-automatic methodology for facial landmark annotation. In
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In: http://ibug.doc.ic.ac.uk/media/uploads/documents/sagonas_cvpr_2013_amfg_w.pdf (2013)
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The first facial expression recognition and analysis challenge
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In: http://ibug.doc.ic.ac.uk/media/uploads/documents/pdf17.pdf (2011)
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| 5 |
Audiovisual discrimination between speech and laughter: Why and when visual information might help
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In: http://ibug.doc.ic.ac.uk/media/uploads/documents/petridispantic_2011_tmm.pdf (2011)
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Classifying laughter and speech using audio-visual feature prediction
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In: http://ibug.doc.ic.ac.uk/media/uploads/documents/ICASSP-2010-PetridisEtAl-CAMERA.pdf (2010)
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Abstract:
In this study, a system that discriminates laughter from speech by modelling the relationship between audio and visual features is presented. The underlying assumption is that this relationship is different between speech and laughter. Neural networks are trained which learn the audio-to-visual and visual-to-audio features mapping for both classes. Classification of a new frame is performed via prediction. All the networks produce a prediction of the expected audio / visual features and the network with the best prediction, i.e., the model which best describes the audiovisual feature relationship, provides its label to the input frame. When trained on a simple dataset and tested on a hard dataset, the proposed approach outperforms audiovisual feature-level fusion, resulting in a 10.9 % and 6.4 % absolute increase in the F1 rate for laughter and classification rate, respectively. This indicates that classification based on prediction can produce a good model even when the available dataset is not challenging enough. Index Terms — laughter-vs-speech discrimination, audiovisual speech / laughter feature relationship, prediction-based classification 1.
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URL: http://ibug.doc.ic.ac.uk/media/uploads/documents/ICASSP-2010-PetridisEtAl-CAMERA.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.370.9928
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Static vs. Dynamic Modeling of Human Nonverbal Behavior from Multiple Cues and Modalities
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In: http://www.doc.ic.ac.uk/~maja/ICMI-2009-PetridisEtAl-CAMERA.pdf (2009)
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A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions
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In: http://www.doc.ic.ac.uk/~maja/PAMI-AVemotionSurvey-CAMERA.pdf (2009)
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| 10 |
Social Signal Processing: Survey of an Emerging Domain
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In: http://www.idiap.ch/~vincia/papers/sspsurvey.pdf (2008)
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Social Signal Processing: State-of-the-art and future perspectives of an emerging domain
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In: http://www.idiap.ch/~vincia/papers/bravetopic.pdf (2008)
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Social Signal Processing: State-of-the-art and future perspectives of an emerging domain
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In: http://www.doc.ic.ac.uk/~maja/ACM-MM-2008-VinciarelliEtAl-CAMERA.pdf (2008)
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| 13 |
Social Signal Processing: Survey of an Emerging Domain
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In: http://www.doc.ic.ac.uk/~maja/IVCJ-SSPsurvey-FINAL.pdf (2008)
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Fusion of audio and visual cues for laughter detection
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In: http://www.doc.ic.ac.uk/~maja/CIVR-2008-PetridisPantic-CAMERA.pdf (2008)
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| 15 |
Facial Action Recognition for Facial Expression Analysis from Static Face Images
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In: http://www.kbs.twi.tudelft.nl/People/Staff/M.Pantic/SMCB-2004-final.pdf (2004)
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20 Machine Analysis of Facial Expressions 1. Human Face and Its Expression
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In: http://s.i-techonline.com/Book/Face-Recognition/ISBN978-3-902613-03-5-fr20.pdf
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| 17 |
VISUAL-ONLY DISCRIMINATION BETWEEN NATIVE AND NON-NATIVE SPEECH
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In: http://ibug.doc.ic.ac.uk/media/uploads/documents/georgakisetal_visualonlynativevsnonnative.pdf
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| 18 |
20 Machine Analysis of Facial Expressions 1. Human Face and Its Expression
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In: http://mplab.ucsd.edu/~marni/pubs/panticbartlett_2007.pdf
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20 Machine Analysis of Facial Expressions 1. Human Face and Its Expression
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In: http://www.doc.ic.ac.uk/~maja/PanticBartlett-Chapter-Proof2.pdf
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| 20 |
Social Signal Processing: The Research Agenda
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In: http://ibug.doc.ic.ac.uk/media/uploads/documents/looking@people-panticetal-revision-final.pdf
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