One of the main spatial audio topics, nowadays, involves working towards an efficient individualization method of Head Related Transfer Functions. A major limitation in this area of research is the lack of a large and uniform database that will incorporate as many individualized properties as possible. This paper presents the MARL-NYU file format for storing HRTF datasets, and investigates the necessary normalization steps that assure a uniform and standardized HRTF repository, by compiling selected datasets from four HRTF databases.
Click to purchase paper as a non-member 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 and is free for AES members and E-Library subscribers.