Utilize este identificador para referenciar este registo:
http://hdl.handle.net/10773/33103
Título: | Understanding public speakers’ performance: first contributions to support a computational approach |
Autor: | Barros, Fábio Conde, Ângelo Soares, Sandra C. Neves, António J. R. Silva, Samuel |
Palavras-chave: | Verbal and non-verbal communication Computational methods Posture Facial expressions Voice |
Data: | 2020 |
Editora: | Springer |
Resumo: | Communication is part of our everyday life and our ability to communicate can have a significant role in a variety of contexts in our personal, academic, and professional lives. For long, the characterization of what is a good communicator has been subject to research and debate by several areas, particularly in Education, with a focus on improving the performance of teachers. In this context, the literature suggests that the ability to communicate is not only defined by the verbal component, but also by a plethora of non-verbal contributions providing redundant or complementary information, and, sometimes, being the message itself. However, even though we can recognize a good or bad communicator, objectively, little is known about what aspects – and to what extent—define the quality of a presentation. The goal of this work is to create the grounds to support the study of the defining characteristics of a good communicator in a more systematic and objective form. To this end, we conceptualize and provide a first prototype for a computational approach to characterize the different elements that are involved in communication, from audiovisual data, illustrating the outcomes and applicability of the proposed methods on a video database of public speakers. |
Peer review: | yes |
URI: | http://hdl.handle.net/10773/33103 |
DOI: | 10.1007/978-3-030-50347-5_30 |
ISBN: | 978-3-030-50346-8 |
ISSN: | 0302-9743 |
Aparece nas coleções: | CIDTFF - Capítulo de livro DEP - Capítulo de livro DETI - Capítulo de livro IEETA - Capítulo de livro WJCR - Capítulo de livro |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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ICIAR2020 Speaker_Performance.pdf | 6.62 MB | Adobe PDF | Ver/Abrir |
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