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Durham University



Publication details for Professor Tuomas Eerola

Lartillot, O., Eerola, T., Toiviainen, P. & Fornari, J. (2008), Multi-feature modeling of pulse clarity: Design, validation, and optimization, in Kim, Youngmoo eds, ISMIR 2008 International Conference on Music Information Retrieval. Philadelphia, PA, 521-526.

Author(s) from Durham


Pulse clarity is considered as a high-level musical dimension
that conveys how easily in a given musical piece, or a
particular moment during that piece, listeners can perceive
the underlying rhythmic or metrical pulsation. The objective
of this study is to establish a composite model explaining
pulse clarity judgments from the analysis of audio recordings.
A dozen of descriptors have been designed, some of
them dedicated to low-level characterizations of the onset
detection curve, whereas the major part concentrates on descriptions
of the periodicities developed throughout the temporal
evolution of music. A high number of variants have
been derived from the systematic exploration of alternative
methods proposed in the literature on onset detection curve
estimation. To evaluate the pulse clarity model and select
the best predictors, 25 participants have rated the pulse clarity
of one hundred excerpts from movie soundtracks. The
mapping between the model predictions and the ratings was
carried out via regressions. Nearly a half of listeners’ rating
variance can be explained via a combination of periodicitybased