If you go to Amazon.com or the Apple Itunes store, your ability to search for new music will largely be limited by the `query-by-metadata' paradigm: search by song, artist or album name. However, when we talk or write about music, we use a rich vocabulary of semantic concepts to convey our listening experience. If we can model a relationship between these concepts and the audio content, then we can produce a more flexible music search engine based on a 'query-by-semantic- description' paradigm. In this talk, I will present a computer audition system that can both annotate novel audio tracks with semantically meaningful words and retrieve relevant tracks from a database of unlabeled audio content given a text-base query.
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