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

ABSTRACT

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.

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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.8 Database applications
          Subjects: Data mining

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.1 Content Analysis and Indexing
          Subjects: Indexing methods
      H.3.3 Information Search and Retrieval
          Subjects: Retrieval models; Clustering; Relevance feedback
      H.3.7 Digital Libraries
          Subjects: Systems issues

General Terms:
Algorithms, Design, Documentation, Experimentation, Legal Aspects, Management, Measurement, Verification

Keywords:
music digital library, music information retrieval, query-by-example, solo voice modeling, vocal/non-vocal segmentation