On the extraction of vocal-related information to facilitate the management of popular music collections

With the explosive growth of networked collections of musical material, there is a need to establish a mechanism like a digital library to manage music data. This paper presents a content-based processing paradigm of popular song collections to facilitate the realization of a music digital library. The paradigm is built on the automatic extraction of information of interest from music audio signals. Because the vocal part is often the heart of a popular song, we focus on developing techniques to exploit the solo vocal signals underlying an accompanied performance. This supports the necessary functions of a music digital library, namely, music data organization, music information retrieval/recommendation, and copyright protection