Head-Related Transfer Function Personalization Based on Modified Sparse Representation with Matching in a Database of Chinese Pilots

Abstract

A new method of head-related transfer function (HRTF) personalization was built to optimize new user matching in the HRTF database to enhance 3D virtual hearing. The method of modified sparse representation (MSR) treated the HRTF personalization for an incomer as the task of finding similar subjects in the HRTF database with sparse representation (SR) of the incomer’s anthropometric features under the assumption that the equivalent sparse combination expresses the same anthropometric features and HRTFs for virtual hearing. The correlations among principal component coefficients and all anthropometric parameters were calculated after principal component analysis of the HRTF database for the same orientation. A derived database of anthropometric parameters was reconstructed, and SR was performed for all subjects in the original HRTF database. When the SR of the incomer was best matched with that of a subject in the derived database, the HRTF of the matched subject was used for the incomer’s 3D virtual hearing. The effect of MSR HRTF personalization was evaluated by spectral distortion. The results showed that the proposed method performed better than the others with the Chinese pilots database and the CIPIC database, especially in the frequency range of 0–8 kHz.