Title :
Speaker age estimation using Hidden Markov Model weight supervectors
Author :
Bahari, Mohamad Hasan ; Van hamme, Hugo
Author_Institution :
Dept. of Electr. Eng. (ESAT), KU Leuven, Leuven, Belgium
Abstract :
This paper proposes a new approach for speaker age estimation. In this method, speakers are modeled by their corresponding Hidden Markov Model (HMM) weight supervectors. Then, Weighted Supervised Non-Negative Matrix Factorization (WSNMF) is applied to reduce the dimension of the input space. Finally, a Least Squares Support Vector Regressor (LS-SVR) is employed to estimate the age of speakers using the obtained low-dimensional vectors. Evaluation results on a corpus of read and spontaneous speech in Dutch confirms the effectiveness of the proposed scheme.
Keywords :
age issues; hidden Markov models; least squares approximations; matrix decomposition; regression analysis; speaker recognition; vectors; Dutch; HMM weight supervectors; LS-SVR; WSNMF; hidden Markov model weight supervectors; input space dimension reduction; least squares support vector regressor; low-dimensional vectors; speaker age estimation; weighted supervised nonnegative matrix factorization; Acoustics; Estimation; Hidden Markov models; Speech; Support vector machines; Training; Wireless sensor networks; Least Squares Support Vector Regressor; speaker age estimation; weighted supervised non-negative matrix factorization;
Conference_Titel :
Information Science, Signal Processing and their Applications (ISSPA), 2012 11th International Conference on
Conference_Location :
Montreal, QC
Print_ISBN :
978-1-4673-0381-1
Electronic_ISBN :
978-1-4673-0380-4
DOI :
10.1109/ISSPA.2012.6310606
