Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: On the Determination of Optimal Model Order for GMM-Based Text-Independent Speaker Identification | EURASIP Journal on Applied Signal Processing 2004 8 1078-1087 2004 Hindawi Publishing Corporation On the Determination of Optimal Model Order for GMM-Based Text-Independent Speaker Identification M. F. Abu El-Yazeed Department of Electronics Communications Engineering Faculty of Engineering Cairo University 12211 Giza Egypt Email elbarawy@ M. A. El Gamal Department of Engineering Physics Mathematics Faculty of Engineering Cairo University 12211 Giza Egypt Email mhgamal@ . ElAyadi Department of Engineering Physics Mathematics Faculty of Engineering Cairo University 12211 Giza Egypt Email mzjeEayadi@ Received 1 October 2003 Revised 9 December 2003 Recommended for Publication by Chin-Hui Lee Gaussian mixture models GMMs are recently employed to provide a robust technique for speaker identification. The determination of the appropriate number of Gaussian components in a model for adequate speaker representation is a crucial but difficult problem. This number is in fact speaker dependent. Therefore assuming a fixed number of Gaussian components for all speakers is not justified. In this paper we develop a procedure for roughly estimating the maximum possible model order above which the estimation of model parameters becomes unreliable. In addition a theoretical measure namely a goodness of fit GOF measure is derived and utilized in estimating the number of Gaussian components needed to characterize different speakers. The estimation is carried out by exploiting the distribution of the training data for each speaker. Experimental results indicate that the proposed technique provides results comparable to other well-known model selection criteria like the minimum description length MDL and the Akaike information criterion AIC . Keywords and phrases Gaussian mixture model goodness of fit minimum description length Akaike information criterion speaker identification text-independent speaker identification. 1. INTRODUCTION Speech .
