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Abstract

Music websites are ubiquitous, and music downloads, such as MP3, are a major source of Web traffic. As the amount of musical content increases and the Web becomes an important mechanism for distributing music, we expect to see a rising demand for music search services. Many currently available music search engines rely on file names, song title, composer or performer as the indexing and retrieval mechanism. These systems do not make use of the musical content. We believe that a more natural, effective, and usable music-information retrieval (MIR) system should have audio input, where the user can query with musical content. We are developing a system called MusArt for audio-input MIR. With MusArt, as with other audio-input MIR systems, a user sings or plays a theme, hook, or riff from the desired piece of music. The system transcribes the query and searches for related themes in a database, returning the most similar themes, given some measure of similarity. We call this "retrieval by query." In this paper, we describe the architecture of MusArt. An important element of MusArt is metadata creation: we believe that it is essential to automatically abstract important musical elements, particularly themes. Theme extraction is performed by a subsystem called MME, which we describe later in this paper. Another important element of MusArt is its support for a variety of search engines, as we believe that MIR is too complex for a single approach to work for all queries. Currently, MusArt supports a dynamic time-warping search engine that has high recall, and a complementary stochastic search engine that searches over themes, emphasizing speed and relevancy. The stochastic search engine is discussed in this paper.