Title :
Neural network model of binaural hearing based on spatial feature extraction of the head related transfer function
Author :
Wu, Zhenyang ; Weng, Tao ; Wang, Weibin ; Lo, T.F. ; Chan, H.Y. ; Lam, F.K.
Author_Institution :
Dept. of Radio Eng., Southeast Univ., Nanjing, China
fDate :
29 Oct-1 Nov 1998
Abstract :
In spatial hearing, complex valued head-related transfer function (HRTF) can be represented as a real valued head-related impulse response (HRIR). Using Karhunen-Loeve expansion, the spatial features of the normalized HRIRs on measurement space can be extracted as spatial character functions. A neural network model based on Von-Mises function is used to approximate the discrete spatial character function of HRIR. As a result, a time-domain binaural model is established and it fits the measured HRIRs well
Keywords :
backpropagation; feature extraction; hearing; neural nets; physiological models; principal component analysis; transfer functions; transient response; Karhunen-Loeve expansion; Von-Mises function; backpropagation; binaural hearing; discrete spatial character function; head related transfer function; hearing space; inverse filter; neural network model; principal components analysis; real valued head-related impulse response; spatial character functions; spatial feature extraction; spatial hearing; speaker response; time-domain binaural model; virtual auditory space; Auditory system; Ear; Extraterrestrial measurements; Feature extraction; Interpolation; Loudspeakers; Neural networks; Pollution measurement; Principal component analysis; Transfer functions;
Conference_Titel :
Engineering in Medicine and Biology Society, 1998. Proceedings of the 20th Annual International Conference of the IEEE
Conference_Location :
Hong Kong
Print_ISBN :
0-7803-5164-9
DOI :
10.1109/IEMBS.1998.747065
