Eyes4Ears - More than a Classical Music Retrieval System

Content-based similarity search for music retrieval attracted a lot attention in recent information retrieval research. Most music applications (e.g. several commercial web portals) offer to search music files, which however is limited to key-word-based search on subjects like genre or artist. Other similarity search approaches base on abstract metrics, which are defined on feature vectors representing psycho-acoustic or physical properties. However, it is still an open problem to adapt the search towards the user own music similarity measure. This paper presents a new music retrieval system which is more than a classical music management system. The system architecture is based on a client/server architecture and offers methods to manage a large music database efficiently. In addition to key-word-based search methods the Eyes4Ears system provides also methods for content-based similarity search. Furthermore, we report an attempt to cross the semantic chasm between user and search system by an adaptive retrieval approach.