Distinguishing the Communicative Functions of Gestures

Authors:
Kristiina Jokinen;Costanza Navarretta;Patrizia Paggio
Affiliations:
University of Tartu and University of Helsinki,;University of Copenhagen, CST;University of Copenhagen, CST
Venue:
MLMI '08 Proceedings of the 5th international workshop on Machine Learning for Multimodal Interaction
Year:
2008

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Abstract

This paper deals with the results of a machine learning experiment conducted on annotated gesture data from two case studies (Danish and Estonian). The data concern mainly facial displays, that are annotated with attributes relating to shape and dynamics, as well as communicative function. The results of the experiments show that the granularity of the attributes used seems appropriate for the task of distinguishing the desired communicative functions. This is a promising result in view of a future automation of the annotation task.