Music Boundary Detection Using Similarity in a Music Selection

This paper proposes a new method of extracting music boundaries, such as a boundary between musical selections, or a boundary between a musical selection and a speech, for automatic segmentation of ideo data and other applications. The method utilizes acoustic similarity in a music selection. Similar partial sections are first extracted, by means of a new algorithm called Segmental Continuous Dynamic Programming, or Segmental CDP. The music boundary is identified by reference to multiple similar sections and their location information, as extracted by Segmental CDP. The performance of the proposed method is evaluated for music boundary extraction using actual music data sets. The study demonstrates that the proposed method enables to extract music boundaries well for both evaluation data and a real broadcasted music program.