| Title | Scale Degree Profiles from Audio Investigated with Machine Learning |
| Publication Type | Conference Paper |
| Year of Publication | 2004 |
| Conference Name | Audio Engineering Society Convention |
| Authors | Purwins, H., Blankertz B., Dornhege G., & Obermayer K. |
| Conference Location | Berlin |
| Keywords | composer classification, harmonic pitch class profiles, music visualization, style |
| Abstract | In this paper we introduce and explore a method for extracting low dimensional features from digitized
recordings of music performance: The so called constant Q scale degree proriles are 12-dimensional
vectors that reflect the prominence of the 12 scale degrees in a section of a piece of music they are
extracted from. Here we study the type and amount of information that is captured in those profiles
when calculated from whole short pieces of piano music. The analyzed data encompass sets of preludes
and fugues by Bach (WTC), Chopin (op. 28), Alkan (op. 31), Scriabin (op. 11), Shostakovich (op. 34),
and Hindemith (Ludus Tonalis). In a supervised approach we investigated the ability of classifiers
to recognize composers from proles. As unsupervised methods we performed (1) a cluster analysis
which resulted in one major and one minor cluster and indicated major/minor ambiguity and how
clearly composers separate between major and minor, and (2) a visualization technique called Isomap
which reveals in its 2-dimensional representation the degree of chromaticism of pieces apart from the
major–minor duality. In summary it is astonishing how much information on a music piece is contained
in the 12-dimensional profiles that can be calculated in a straight-forward manner from any digitized
music recording.
|
| Full Document | http://mtg.upf.edu/files/publications/pur04bProfMLAES.pdf |
