Fast modelling of pinna spectral notches from HRTFs using linear prediction residual cepstrum

Developing individualized head related transfer functions (HRTF) is an essential requirement for accurate virtualization of sound. However it is time consuming and complicated for both the subject and the developer. Obtaining the spectral notches which are the most prominent features of HRTF is very important to reconstruct the head related impulse response (HRIR) accurately. In this paper, a method suitable for fast computation of the frequencies of spectral notches is proposed. The linear prediction residual cepstrum is used to compute the spectral notches with a high degree of accuracy in this work. Subsequent use of Batteaus Reflection model to overlay the spectral notches on the pinna images indicate that the proposed method is able to provide finer contours. Experiments on reconstruction of the HRIR indicates that the method performs better than other methods.