D. Meredith, G. Wiggins, and K. Lemstrom. Pattern induction and matching in polyphonic music and other multidimensional datasets. In Proc. Conference on Systemics, Cybernetics and Informatics, volume X, pages 61--66, 2001. Home/Search Document Details and Download
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Sweepline the Music! - Ukkonen, Lemström, Mäkinen Self-citation (Lemstrm) (Correct)
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D. Meredith, G.A. Wiggins, and K. Lemstrm. Pattern induction and matching in polyphonic music and other multi-dimensional data. In the 5th World Multi-Conference on Systemics, Cybernetics and Informatics (SCI'2001), volume X, pages 61--66, 2001.
A Three-Layer Approach for Music Retrieval in Large.. - Lemström, Wiggins, Meredith Self-citation (Meredith Wiggins Lemstrom) (Correct)
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D. Meredith, G.A. Wiggins and K. Lemstrom. Pattern induction and matching in polyphonic music and other multidimensional datasets. In Proceedings of the Fifth World Multiconference on Systemics Cybernetics and Informatics (SCI
A Three-Layer Approach for Music Retrieval in Large Databases - Lemström, Wiggins (2001) Self-citation (Meredith Wiggins Lemstr) (Correct)
....previously suggested for MIR indexing, havebeen alike in that they have been based on sequences of musical events, and the sequences to be considered have been xed beforehand. Our current pattern induction algorithm, ###### (Structure Induction Algorithm with Translational Equivalence Classes) [6], can be used to nd the frequently occurring musical patterns. ###### works in two phases. The rst phase, ###, computes every maximal repeated pattern in the given music database. The second phase takes the output of ### as input and then computes all the occurrences of each of the maximal ....
....frequently applied to MIR (see e.g. 4] for a summary of some current methods) The found occurrences, however, for this layer are always sequential. Therefore wehave one further layer. The Third Layer The nal third layer applies the ######### matching algorithm based on the ### algorithm [6]. This layer is the slowest of the three, but it allows a broader de nition of what counts as a possible match than the two previous layers. More precisely, it does the same kind of LCTS matching as the rst layer, but because it does not need the indexing structure, it is not restricted to ....
D. Meredith, G.A. Wiggins and K. Lemstrom. Pattern induction and matching in polyphonic music and other multidimensional datasets. In ########### ## ### ##### ##### ############### ## ######### ########### ### ########### #########, pages 61-66 (vol X), Orlando, FL, 2001.
A Three-Layer Approach for Music Retrieval in Large Databases - Lemström, Wiggins Self-citation (Meredith Wiggins Lemstr) (Correct)
....previously suggested for MIR indexing, have been alike in that they have been based on sequences of musical events, and the sequences to be considered have been xed beforehand. Our current pattern induction algorithm, SIATEC (Structure Induction Algorithm with Translational Equivalence Classes) [6], can be used to nd the frequently occurring musical patterns. SIATEC works in two phases. The rst phase, SIA, computes every maximal repeated pattern in the given music database. The second phase takes the output of SIA as input and then computes all the occurrences of each of the maximal ....
....frequently applied to MIR (see e.g. 4] for a summary of some current methods) The found occurrences, however, for this layer are always sequential. Therefore we have one further layer. The Third Layer The nal third layer applies the SIA(M)ESE matching algorithm based on the SIA algorithm [6]. This layer is the slowest of the three, but it allows a broader de nition of what counts as a possible match than the two previous layers. More precisely, it does the same kind of LCTS matching as the rst layer, but because it does not need the indexing structure, it is not restricted to ....
D. Meredith, G.A. Wiggins and K. Lemstrom. Pattern induction and matching in polyphonic music and other multidimensional datasets. In Proceedings of the Fifth World Multiconference on Systemics Cybernetics and Informatics (SCI
Representation and Discovery of Vertical Patterns in Music - Conklin (Correct)
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D. Meredith, G. Wiggins, and K. Lemstrom. Pattern induction and matching in polyphonic music and other multidimensional datasets. In Proc. Conference on Systemics, Cybernetics and Informatics, volume X, pages 61--66, 2001.
Harmonic Modeling for Polyphonic Music Retrieval - Pickens (2004) (1 citation) (Correct)
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Meredith, D., Wiggins, G.A., and Lemstrom, K. Pattern induction and matching in polyphonic music and other multi-dimensional datasets. In the 5th World Multi-Conference on Systemics, Cybernetics and Informatics (Orlando, 2001), pp. 61--66.
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