AbstractCommunicative content in human communication involves expressivity of socio-affective
states. Research in Linguistics, Social Signal Processing and Affective Computing in par
ticular, highlights the importance of affect, emotion and attitudes as sources of information for
communicative content. Attitudes, considered as socio-affective states of speakers, are
conveyed through a multitude of signals during communication. Understanding the expres sion of
attitudes of speakers is essential for establishing successful communication. Taking the
empirical approach to studying attitude expressions, the main objective of this research is
to contribute to the development of an automatic attitude classification system through a
fusion of multimodal signals expressed by speakers in video biogs. The present study de
scribes a new communicative genre of self-expres.....