InteSe: An Integrated Model for Resolving Ambiguities in Multimodal Sentences

被引:16
|
作者
Caschera, Maria Chiara [1 ]
Ferri, Fernando [1 ]
Grifoni, Patrizia [1 ]
机构
[1] CNR, Inst Res Populat & Social Policies CNR IRPPS, I-00185 Rome, Italy
关键词
Hidden Markov models (HMMs); human-machine interaction; languages; HIDDEN MARKOV MODEL; DISAMBIGUATION;
D O I
10.1109/TSMCA.2012.2210407
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:911 / 931
页数:21
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