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2009
ACM

Data-driven exploration of musical chord sequences

11 years 7 months ago
Data-driven exploration of musical chord sequences
We present data-driven methods for supporting musical creativity by capturing the statistics of a musical database. Specifically, we introduce a system that supports users in exploring the high-dimensional space of musical chord sequences by parameterizing the variation among chord sequences in popular music. We provide a novel user interface that exposes these learned parameters as control axes, and we propose two automatic approaches for defining these axes. One approach is based on a novel clustering procedure, the other on principal components analysis. A user study compares our approaches for defining control axes both to each other and to an approach based on manually-assigned genre labels. Results show that our automatic methods for defining control axes provide a subjectively better user experience than axes based on manual genre labeling. Author Keywords Creativity, music, chords, genre, PCA, clustering, transition matrix, HMMs ACM Classification Keywords H.5.5. Sound and mus...
Eric Nichols, Dan Morris, Sumit Basu
Added 17 Mar 2010
Updated 17 Mar 2010
Type Conference
Year 2009
Where IUI
Authors Eric Nichols, Dan Morris, Sumit Basu
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