Normalized cuts for predominant melodic source separation

Mathieu Lagrange*, Luis Gustavo Martins, Jennifer Murdoch, George Tzanetakis

*Autor correspondente para este trabalho

Resultado de pesquisarevisão de pares

30 Citações (Scopus)

Resumo

The predominant melodic source, frequently the singing voice, is an important component of musical signals. In this paper, we describe a method for extracting the predominant source and corresponding melody from ldquoreal-worldrdquo polyphonic music. The proposed method is inspired by ideas from computational auditory scene analysis. We formulate predominant melodic source tracking and formation as a graph partitioning problem and solve it using the normalized cut which is a global criterion for segmenting graphs that has been used in computer vision. Sinusoidal modeling is used as the underlying representation. A novel harmonicity cue which we term harmonically wrapped peak similarity is introduced. Experimental results supporting the use of this cue are presented. In addition, we show results for automatic melody extraction using the proposed approach.
Idioma originalEnglish
Número do artigo4432646
Páginas (de-até)278-290
Número de páginas13
RevistaIEEE Transactions on Audio, Speech and Language Processing
Volume16
Número de emissão2
DOIs
Estado da publicaçãoPublicado - fev 2008
Publicado externamenteSim

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