We propose a new approach to a music search engine that can be accessed via natural language queries. As with existing approaches, we try to gather as much contextual information as possible for individual pieces in a (possibly large) music collection by means of Web retrieval. While existing approaches use this textual information to construct representations of music pieces in a vector space model, in this paper, we propose a document-centered technique to retrieve music pieces relevant to arbitrary natural language queries. This technique improves the quality of the resulting document rankings substantially. We report on the current state of the research and discuss current limitations, as well as possible directions to overcome them.
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