Name
Title | ||
|---|---|---|
Individualization of Head Related Transfer Functions Based on Radial Basis Function Neural Network |
Abstract | ||
|---|---|---|
Head Related Transfer Functions (HRTFs) contain sound localization cues and are commonly used in 3D audio reproduction. Due to HRTFs are closely related to anthropometric parameters (head, pinna, torso), which means HRTFs vary with each individual, how to obtain a set of suitable HRTFs for each individual remains to be solved. In this paper, we investigated the complex relationship between HRTFs and anthropometric parameters through Radial Basis Function neural network (RBF), and proposed a method of generating individualized HRTFs with listener's anthropometric parameters. Objective experiments show that the estimated HRTFs have good consistency with measured ones, and the spectral distortion values have an average reduction of 0.59 dB compared with other methods. Subjective listening tests show that using estimated HRTFs enable accurate auditory localization. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/ICME.2018.8486494 | 2018 IEEE International Conference on Multimedia and Expo (ICME) |
Keywords | Field | DocType |
HRTFs,anthropometric parameters,RBF neural network,individualization | Torso,Computer vision,Pattern recognition,Radial basis function neural,Computer science,Auditory localization,Transfer function,Sound localization,Artificial intelligence,Spectral distortion | Conference |
ISSN | ISBN | Citations |
1945-7871 | 978-1-5386-1738-0 | 0 |
PageRank | References | Authors |
0.34 | 1 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lian Meng | 1 | 0 | 0.34 |
| Xiaochen Wang | 2 | 5 | 7.61 |
| Wei Chen | 3 | 86 | 12.45 |
| Chunling Ai | 4 | 0 | 0.68 |
| Ruimin Hu | 5 | 961 | 117.18 |