Perceptual Segment Clustering For Music Description And Time-axis Redundancy Cancellation
نویسنده
چکیده
Repeating sounds and patterns are widely exploited throughout music. However, although analysis and music information retrieval applications are often concerned with processing speed and music description, they typically discard the benefits of sound redundancy cancellation. We propose a perceptually grounded model for describing music as a sequence of labeled sound segments, for reducing data complexity, and for compressing audio.
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