In This Section
Audibility of a CD-Standard A/DA/A Loop Inserted into High-Resolution Audio Playback - September 2007
Sound Board: Food for Thought, Aesthetics in Orchestra Recording - April 2015
Reflecting on Reflections - June 2014
AES Conference Papers Forum
Adaptive Distance Measures for Exploration and Structuring of Music Collections
Music similarity plays an important role in many Music Information Retrieval applications. However, it has many facets and its perception is highly subjective -- very much depending on a person's background or retrieval goal. This paper presents a generalized approach to modeling and learning individual distance measures for comparing music pieces based on multiple facets that can be weighted. The learning process is described as an optimization problem guided by generic distance constraints. Three application scenarios with different objectives exemplify how the proposed method can be employed in various contexts by deriving distance constraints either from domain-specific expert information or user actions in an interactive setting.
No AES members have commented on this paper yet.
Subscribe to this discussion
Start a discussion!
If you are not yet an AES member and have something important to say about this paper then we urge you to join the AES today and make your voice heard. You can join online today by clicking here.