Observing the Clustering Tendencies of Head Related Transfer Function Databases
This study offers a detailed description of the clustering tendencies of a large, standardized HRTF repository, and compares the quality of the results to those of a CIPIC database subset. The statistical analysis was implemented by applying k-means clustering on the log magnitude of HRTFs on the horizontal plane, for a varying number of clusters. A thorough report on the grouping behavior of the filters as the number of clusters increases revealed a superiority of the HRTF repository in describing common behaviors across equivalent azimuth positions, over the CIPIC subset, for the majority of the HRTF datasets.
Click to purchase paper or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!
This paper costs $33 for non-members, $5 for AES members and is free for E-Library subscribers.