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Alessandro Vinciarelli
Researcher at University of Glasgow
Publications - 237
Citations - 8098
Alessandro Vinciarelli is an academic researcher from University of Glasgow. The author has contributed to research in topics: Personality & Nonverbal communication. The author has an hindex of 39, co-authored 226 publications receiving 7180 citations. Previous affiliations of Alessandro Vinciarelli include Roma Tre University & University of Twente.
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Social Signal Processing
TL;DR: It is argued that next-generation computing needs to include the essence of social intelligence - the ability to recognize human social signals and social behaviours like turn taking, politeness, and disagreement - in order to become more effective and more efficient.
Proceedings ArticleDOI
The INTERSPEECH 2013 computational paralinguistics challenge: social signals, conflict, emotion, autism
Björn Schuller,Stefan Steidl,Anton Batliner,Alessandro Vinciarelli,Klaus R. Scherer,Fabien Ringeval,Mohamed Chetouani,Felix Weninger,Florian Eyben,Erik Marchi,Marcello Mortillaro,Hugues Salamin,Anna Polychroniou,Fabio Valente,Samuel Kim +14 more
TL;DR: The INTERSPEECH 2013 Computational Paralinguistics Challenge provides for the first time a unified test-bed for Social Signals such as laughter in speech and introduces conflict in group discussions as a new task and deals with autism and its manifestations in speech.
Journal ArticleDOI
A Survey of Personality Computing
TL;DR: A survey of technologies capable of dealing with human personality, and a conceptual model underlying the three main problems addressed in the literature, namely Automatic Personality Recognition, Automatic Personality Perception and Automatic Personality Synthesis.
Journal ArticleDOI
Bridging the Gap between Social Animal and Unsocial Machine: A Survey of Social Signal Processing
Alessandro Vinciarelli,Maja Pantic,Dirk Heylen,Catherine Pelachaud,Isabella Poggi,Francesca D'Errico,M. Schroeder +6 more
TL;DR: This is the first survey of the domain that jointly considers its three major aspects, namely, modeling, analysis, and synthesis of social behavior, which investigates laws and principles underlying social interaction, and explores approaches for automatic understanding of social exchanges recorded with different sensors.
Journal ArticleDOI
Offline recognition of unconstrained handwritten texts using HMMs and statistical language models
TL;DR: The use of language models is shown to improve the accuracy of the system and the approach is described in detail and compared with other methods presented in the literature to deal with the same problem.