Fuzzy based multi-source data fusion for children's age estimation

Mirhassani, S.M. and Zourmand, A. and Ting, H.N. (2014) Fuzzy based multi-source data fusion for children's age estimation. In: Asia Pacific Conference on Medical and Biological Engineering, 09-12 Oct 2014, Tainan, Taiwan. (Submitted)

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Abstract

Estimation of speaker's age is a challenge in speech processing area. This paper a novel approach for estimating a speaker's age is addressed. The method employs a "divide and conquer" strategy wherein the processing speech data are divided into six groups based on the vowel classes. Afterward, Mel-frequency cepstral coefficients are computed for each group and single layer feed-forward neural networks are applied to the features to make a primary decision. The extreme learning machine (ELM) method is used to train the classifiers. Subsequently, fuzzy data fusion is employed to provide an overall decision by aggregating the classifier's outputs. The results are then compared with vowel independent age estimation based on ELM and other well-known classification methods, including support vector machine and Knearest neighbor. The processing speech data include six Malay vowels collected from 360 Malay children aged between 7 and 12 years. Experiments conducted based on six age groups revealed that fuzzy fusion of the classifier's outputs resulted in considerable improvement of up to 72.63% in age estimation accuracy. Moreover, the fuzzy fusion of decisions aggregated complimentary information of a speaker's age from varied speech sources.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Fuzzy information fusion, extreme learning machine, age estimation, speech processing.
Subjects: T Technology > TP Chemical technology
Divisions: Faculty of Engineering
Depositing User: Mr. Mohd Samsul Ismail
Date Deposited: 18 Dec 2014 03:11
Last Modified: 13 Mar 2015 05:38
URI: http://eprints.um.edu.my/id/eprint/11391

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