In this paper, we propose a framework for investigating the effect that certain design parameters of the traditional bendir frame drum have on its acoustical behavior. The proposed approach aims to assess the validity of several assumptions around frame drum design, which are mainly based on knowledge acquired through years of trial and error. A dataset has been formulated with recorded sound samples from six different bendir frame drums, which were designed and manufactured in a controlled manner with specified parameters for the purpose of conducting comparisons between them. These comparisons involved: a) objective metrics in the form of audio features, which are commonly deployed by machine learning algorithms for recognition and classification tasks, and b) a subjective listening test, in which participants with musical background were asked to evaluate the different designs based on some perceptual characteristics. Preliminary results demonstrate the feasibility of the proposed approach, which may serve as a useful tool for frame drum designers. Furthermore, they motivate its expansion with the investigation of more design parameters aiming at a thorough understanding of frame drum design.
(See document for exact affiliation information.)
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 Join the AES. If you need to check your member status, login to the Member Portal.
