This paper presents two examples of how nonverbal communication can be automatically detected and interpreted in terms of social phenomena. In particular, the presented approaches use simple prosodic features to distinguish between journalists and non-journalists in media, and extract social networks from turn-taking to recognize roles in different interaction settings (broadcast data and meetings). Furthermore, the article outlines some of the most interesting perspectives in this line of research. © 2011 Springer.
CITATION STYLE
Vinciarelli, A., Salamin, H., Mohammadi, G., & Truong, K. (2011). More than words: Inference of socially relevant information from nonverbal vocal cues in speech. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6456 LNCS, pp. 23–33). https://doi.org/10.1007/978-3-642-18184-9_3
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