Audio Effect Classification Based on Auditory Perceptual Attributes
While the classification of audio effects has several applications in music production, the heterogeneity of possible taxonomies, as well as the many viable points of view for organizing effects, present research problems that are not easily solved. Creating extensible Semantic Web ontologies provide a possible solution to this problem. This paper presents the results of a listening test that facilitates the creation of a classification system based on auditory perceptual attributes that are affected by the application of audio effects. The obtained results act as a basis for a classification system to be integrated in a Semantic Web Ontology covering the domain of audio effects in the context of music production.
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 temporarily free for AES members.