TY  - JOUR
AU  - Al-Ani, Muzhir Shaban 
AU  - Mohammed, Thabit Sultan 
AU  - Aljebory, Karim M. 
PY  - 2007
TI  - Speaker Identification: A Hybrid Approach Using Neural Networks and Wavelet Transform 
JF  - Journal of Computer Science
VL  - 3
IS  - 5
DO  - 10.3844/jcssp.2007.304.309
UR  - https://thescipub.com/abstract/jcssp.2007.304.309
AB  - In speaker identification systems, a database is constructed from the speech samples of known speakers. The approach implemented in this paper is hybrid, where the wavelet transform and neural networks are used together to form a system with improved performance. Features are extracted by applying a discrete wavelet transform (DWT), while a neural  network (NN) is used for formulating the system database and for handling the task of decision making. The neural network is trained using inputs, which are  the feature vectors. A criteria depends on both false acceptance ratio (FAR) and false rejection ratio (FRR) is used to evaluate the system performance. For experimenting the proposed system, a set  of 25 randomly aged male and female speakers was used. Results of admitting the members of this set to a secure system were computed and presented. The evaluation criteria parameters obtained are; FAR=14.5% and FRR=24.5%