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InteSe: An integrated model for resolving ambiguities in multimodal sentences

Academic Article
Publication Date:
2013
abstract:
The pervasiveness of ambiguity in communication processes suggests addressing the problem of semantic and syntactic ambiguities in multimodal interaction languages. This paper presents an integrated model based on layered, hierarchical, and hidden Markov models for dealing with the complex process of multimodal ambiguity resolution. The proposed model consists of different levels, from the terminals of a multimodal language (terminal elements) to the level of multimodal sentences. A software module implemented the model that has been evaluated in terms of accuracy and robustness. The experimental results show good levels of accuracy and robustness compared with other existing approaches. © 2013 IEEE.
Iris type:
01.01 Articolo in rivista
Keywords:
Hidden Markov models (HMMs); Human-machine interaction; Languages
List of contributors:
Grifoni, Patrizia; Ferri, Fernando; Caschera, MARIA CHIARA
Authors of the University:
CASCHERA MARIA CHIARA
FERRI FERNANDO
GRIFONI PATRIZIA
Handle:
https://iris.cnr.it/handle/20.500.14243/255573
Published in:
IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS. SYSTEMS
Journal
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http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=6301759
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