0000000000872083
AUTHOR
Martín Ariel Hartmann
showing 2 related works from this author
Testing a spectral-based feature set for audio genre classification
2011
Automatic musical genre classification is an important information retrieval task since it can be applied for practical purposes such as the organization of data collections in the digital music industry. However, this task remains an open question because the current state of the art shows far from satisfactory outcomes in terms of classification performance. Moreover, the most common algorithms that are used for this task are not designed for modelling music perception. This study suggests a framework for testing different musical features for use in music genre classification and evaluates the performance of this task based on two musical descriptors. The focus of this study is on automa…
Modelling and prediction of perceptual segmentation
2017
While listening to music, we somehow make sense of a multiplicity of auditory events; for example, in popular music we are often able to recognize whether the current section is a verse or a chorus, and to identify the boundaries between these segments. This organization occurs at multiple levels, since we can discern motifs, phrases, sections and other groupings. In this work, we understand segment boundaries as instants of significant change. Several studies on music perception and cognition have strived to understand what types of changes are associated with perceptual structure. However, effects of musical training, possible differences between real-time and non real-time segmentation, and…