Blackburn, Steven G. Content Based Retrieval and Navigation of Music, 1999. Mini-thesis, University of Southampton. @ NUS Home/Search Document Details and Download
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A Survey of Feature Selection Techniques for Music Information.. - Pickens (2001) (2 citations) (Correct)
....but they must still start and finish at the same time. Polyphonic music adds yet another complication. A note may begin before a previous note finishes. Feature extraction can be thought of as representation conversion, taking low level representation and identifying higher level features [6]. Features at one level may build upon features at a lower level. The techniques employed range from string matching algorithms familiar to a computer scientist to deep structure approaches more familiar to a music theorist. The goal, however, is not an understanding of music. It is not to ....
....time [32] such features are rich enough. However, other retrieval approaches require larger basic features. Longer sequences, or n grams, are constructed from an initial sequence of interval or ratio unigrams. One of the simpler approaches to n gram extraction is the use of sliding windows [16, 6]. The sequence of notes within a length window are converted to a sequence of relative unigrams. Numerous authors suggest a tradeoff between unigram type and n gram size. Where more precise (exact magnitude) unigrams are used, ngrams remain shorter, perhaps not to sacrifice recall. Where more ....
S. G. Blackburn. Content based retrieval and navigation of music, 1999. Mini-thesis, University of Southampton.
Harmonic Modeling for Polyphonic Music Retrieval - Pickens (2004) (1 citation) (Correct)
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Blackburn, Steven G. Content Based Retrieval and Navigation of Music, 1999. Mini-thesis, University of Southampton.
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