Abstract
To individualize head-related transfer function (HRTF) fast and effectively, this paper presents a database matching method based on the similarity and the relativity of anthropometric structures, combined with the methods of principal component analysis (PCA) and multiple linear regression (MLR). The matched HRTF is compared with that of KEMAR dummy head in the subjective listening experiments. Results show that the matched HRTF can enhance the localization accuracy and abate the rate of front-back confusion.
| Original language | English |
|---|---|
| Pages (from-to) | 783-787 |
| Number of pages | 5 |
| Journal | Shuju Caiji Yu Chuli/Journal of Data Acquisition and Processing |
| Volume | 25 |
| Issue number | 6 |
| State | Published - Nov 2010 |
Keywords
- Database matching
- Head-related transfer function(HRTF)
- Principal component analysis