Modelling and prediction of perceptual segmentation
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 the relative importance of different musical dimensions on perception
and prediction of segmentation are still unsolved problems. Investigating these
issues can lead to a better understanding of mechanisms used by different types of
listeners in different contexts, and to gain knowledge of the relationship between
perceptual structure and underlying acoustic changes in the music.
In this work, we collected segmentation responses from musical pieces in two
listening experiments, a real-time task and a non real-time task. Boundary data
was obtained from 18 non-musicians in the real-time task and from 18 musicians
in both tasks. We used kernel density estimation to aggregate boundary responses
from multiple participants into a perceptual segment density curve, and novelty
detection to obtain computational models based on audio musical features extracted from the musical stimuli.
Overall, our findings provide evidence for an effect of experimental task on perceptual segmentation and its prediction, and clarify the contribution of local and
global musical characteristics. However, the findings do not resolve discrepancies
in the literature regarding musicianship. Furthermore, this investigation highlights the role of local musical change between homogeneous regions in boundary
perception, the impact of boundary indication delays on segmentation, and the
problem of segmentation time scales on modelling.
...
Julkaisija
University of JyväskyläISBN
978-951-39-6903-5ISSN Hae Julkaisufoorumista
1459-4331Asiasanat
Metadata
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