Institute of Electrical and Electronics Engineers Inc.;New York: IEEE
摘要:
摘要： This work presents an access control system, which is a speaker identification system based on whispered speech. Speaker identification is a main function of an access control system. Hence, a novel speaker identification system using instantaneous frequencies is proposed. The input speech signals pass through both signal independent and signal dependent filters firstly. Then, we derive the signal's instantaneous frequencies by applying the Hilbert transform. The analyzed instantaneous frequencies are proceeded to be modeled as probability density models. We use these probability density models as the feature in the proposed speaker identification system. In this work, we compare the use of parametric and nonparametric probability density estimation for instantaneous frequency modeling. Furthermore, we propose an approximated probability product kernel support vector machine (APPKSVM). In the APPKSVM, Riemann sum is applied in approximating the probability product kernel. The whisper sounds from the CHAIN speech corpus were used in the experiments. Results of the experiments show the superiority of the proposed speaker identification system. 其他題名： TASE 出版者： New York: IEEE 出版日期： 2015-10-01 出處： IEEE transactions on automation science and engineering, 2015-10, Vol.12 (4), p.1191-1199 資源來源： IEEE Xplore 版權： Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Oct 2015 識別號： ISSN: 1545-5955 識別號： EISSN: 1558-3783 識別號： DOI: 10.1109/TASE.2015.2467311 識別號： CODEN: ITASC7
