A preliminary study on attitude recognition from speaker’s orofacial motions using random forest classifier

Puyang Geng; Shaopei Shi; Hong Guo

doi:10.1117/12.2599383

30 June 2021 A preliminary study on attitude recognition from speaker’s orofacial motions using random forest classifier

Puyang Geng, Shaopei Shi, Hong Guo

Author Affiliations +

Proceedings Volume 11878, Thirteenth International Conference on Digital Image Processing (ICDIP 2021); 1187805 (2021) https://doi.org/10.1117/12.2599383
Event: Thirteenth International Conference on Digital Image Processing, 2021, Singapore, Singapore

Abstract

Purpose: The current study aims to investigate the effect of orofacial motions for automatic attitude recognition Method: To achieve this goal, the movements of lips and jaw during the expressions of six common attitudes from 33 native Mandarin Chinese speakers were collected using ElectroMegnatic Articulography. The random forest classifications were then conducted for attitude recognition based on orofacial data. Results: the average rate of attitude recognition was 63.45%, and the identification accuracy was above 60% for almost every attitude. Besides, for the further classifications separately conducting on each pair of attitudes, the opposing attitudes within each attitude pair were all reasonably recognized (i.e., above 65%). Conclusion: The use of orofacial expressions in attitude expression could be valuable features for the technology of automatic attitude recognition.

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Puyang Geng, Shaopei Shi, and Hong Guo "A preliminary study on attitude recognition from speaker’s orofacial motions using random forest classifier", Proc. SPIE 11878, Thirteenth International Conference on Digital Image Processing (ICDIP 2021), 1187805 (30 June 2021); https://doi.org/10.1117/12.2599383

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