TY - GEN
T1 - A study on GMM-SVM with adaptive relevance factor and its comparison with i-vector and JFA for speaker recognition
AU - You, Chang Huai
AU - Li, Haizhou
AU - Ma, Bin
AU - Lee, Kong Aik
PY - 2013/10/18
Y1 - 2013/10/18
N2 - Recently, joint factor analysis (JFA) and identity-vector (i-vector) represent the dominant techniques used for speaker recognition due to their superior performance. Developed relatively earlier, the Gaussian mixture model - support vector machine (GMM-SVM) with nuisance attribute projection (NAP) has gradually become less popular. However, when developing the relevance factor in maximum a posteriori (MAP) estimation of GMM to be adapted by application data in place of the conventional fixed value, it is noted that GMM-SVM demonstrates some advantages. In this paper, we conduct a comparative study between GMM-SVM with adaptive relevance factor and JFA/i-vector under the framework of Speaker Recognition Evaluation (SRE) formulated by the National Institute of Standards and Technology (NIST).
AB - Recently, joint factor analysis (JFA) and identity-vector (i-vector) represent the dominant techniques used for speaker recognition due to their superior performance. Developed relatively earlier, the Gaussian mixture model - support vector machine (GMM-SVM) with nuisance attribute projection (NAP) has gradually become less popular. However, when developing the relevance factor in maximum a posteriori (MAP) estimation of GMM to be adapted by application data in place of the conventional fixed value, it is noted that GMM-SVM demonstrates some advantages. In this paper, we conduct a comparative study between GMM-SVM with adaptive relevance factor and JFA/i-vector under the framework of Speaker Recognition Evaluation (SRE) formulated by the National Institute of Standards and Technology (NIST).
KW - Gaussian mixture model
KW - i-vector
KW - joint factor analysis
KW - maximum a posteriori
KW - PLDA
KW - support vector machine
UR - http://www.scopus.com/inward/record.url?scp=84890533475&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2013.6639158
DO - 10.1109/ICASSP.2013.6639158
M3 - Conference article published in proceeding or book
AN - SCOPUS:84890533475
SN - 9781479903566
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 7683
EP - 7687
BT - 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
T2 - 2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
Y2 - 26 May 2013 through 31 May 2013
ER -