Empirical Musicology Review: Volume 5, Number 4 (2010)

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https://kb.osu.edu/handle/1811/81092

Empirical Musicology Review Vol. 5, No. 4, 2010

Issue DOI: https://doi.org/10.18061/1811/81092

Editor's Note
Keller, Peter E. p. 120
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Using Automated Rhyme Detection to Characterize Rhyming Style in Rap Music
Hirjee, Hussein; Brown, Daniel pp. 121-145
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Lure(d) into listening: The potential of cognition-based music information retrieval
Honing, Henkjan pp. 146-151
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Time Series Analysis as a Method to Examine Acoustical Influences on Real-time Perception of Music
Dean, Roger T.; Bailes, Freya pp. 152-175
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Hooked on Music Information Retrieval
de Haas, W. Bas; Wiering, Frans pp. 176-185
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Third International Conference of Students of Systematic Musicology (SysMus10): A Conference Report
Jukic, Nina; Küssner, Mats; Wang, Li-ching pp. 186-190
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Announcements
Keller, Peter E. pp. 191-194
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Now showing 1 - 7 of 7

Announcements
(Empirical Musicology Review, 2010-10) Keller, Peter E.
Third International Conference of Students of Systematic Musicology (SysMus10): A Conference Report
(Empirical Musicology Review, 2010-10) Jukic, Nina; Küssner, Mats; Wang, Li-ching
SysMus10, the third International Conference of Students of Systematic Musicology, was held at the University of Cambridge, UK, in September 2010. The conference was organised by PhD students at the Centre for Music and Science in the University’s Faculty of Music. SysMus10 brought together around 40 advanced students working in the field of systematic musicology representing 14 nationalities. The presentations primarily focused on the students’ ongoing research for their PhDs or Masters’ degrees. The conference included the presentation and publication of 25 peer- reviewed papers and posters, keynotes from top researchers in the field (Eric Clarke, Nicholas Cook, and Petri Toiviainen), a workshop and several social activities. Although the conference revealed that the concept of “systematic musicology” is still not known much outside the German-speaking research community, it served as an excellent exchange platform for students doing music research in various disciplines. SysMus10 successfully continued the strong work of the first two SysMus conferences (SysMus08, held in Graz, Austria, and SysMus09, held in Ghent, Belgium), and no doubt next year’s conference, SysMus11 (to be held in Cologne, Germany), will be just as enlightening and inspiring for young musicologists and students of other fields alike.
Hooked on Music Information Retrieval
(Empirical Musicology Review, 2010-10) de Haas, W. Bas; Wiering, Frans
This article provides a reply to 'Lure(d) into listening: The potential of cognition-based music information retrieval,' in which Henkjan Honing discusses the potential impact of his proposed Listen, Lure & Locate project on Music Information Retrieval (MIR). Honing presents some critical remarks on data-oriented approaches in MIR, which we endorse. To place these remarks in context, we first give a brief overview of the state of the art of MIR research. Then we present a series of arguments that show why purely data-oriented approaches are unlikely to take MIR research and applications to a more advanced level. Next, we propose our view on MIR research, in which the modelling of musical knowledge has a central role. Finally, we elaborate on the ideas in Honing's paper from a MIR perspective in this paper and propose some additions to the Listen, Lure & Locate project.
Time Series Analysis as a Method to Examine Acoustical Influences on Real-time Perception of Music
(Empirical Musicology Review, 2010-10) Dean, Roger T.; Bailes, Freya
Multivariate analyses of dynamic correlations between continuous acoustic properties (intensity and spectral flatness) and real-time listener perceptions of change and expressed affect (arousal and valence) in music are developed, by an extensive application of autoregressive Time Series Analysis (TSA). TSA offers a large suite of techniques for modeling autocorrelated time series, such as constitute both music’s acoustic properties and its perceptual impacts. A logical analysis sequence from autoregressive integrated moving average regression with exogenous variables (ARIMAX), to vector autoregression (VAR) is established. Information criteria discriminate amongst models, and Granger Causality indicates whether a correlation might be a causal one. A 3 min electroacoustic extract from Wishart’s Red Bird is studied. It contains digitally generated and transformed sounds, and animate sounds, and our approach also permits an analysis of their impulse action on the temporal evolution and the variance in the perceptual time series. Intensity influences perceptions of change and expressed arousal substantially. Spectral flatness influences valence, while animate sounds influence the valence response and its variance. This TSA approach is applicable to a wide range of questions concerning acoustic- perceptual relationships in music.
Lure(d) into listening: The potential of cognition-based music information retrieval
(Empirical Musicology Review, 2010-10) Honing, Henkjan
This paper argues for the potential of cognition-based music retrieval by introducing the notion of a musical ‘hook’ as a key memorization, recall, and search mechanism. A hook is considered the most salient, memorable, and easy to recall moment of a musical phrase or song. Next to its role in searching large data-bases of music, it is proposed as a way to understand and identify which cognitively relevant musical features affect the appreciation, memorization and recall of music. To illustrate the potential of this idea for the computational humanities (Willekens et al., 2010), in the second half of the paper a pilot research project is described. This project, named Listen, Lure & Locate, aims to study the cultural phenomenon of being lured to listen to new unfamiliar music, and especially the role that recent internet-mediated technologies can have in this process. It is argued that a combination of crowd annotation (i.e., social- or crowd-tagging) and marking the specific moment (the hook) in one’s favorite music, has great potential for improving search engines for music. In addition, these annotations will provide a rich empirical source to music cognition research in determining what makes certain melodic fragments more sticky than others.
Using Automated Rhyme Detection to Characterize Rhyming Style in Rap Music
(Empirical Musicology Review, 2010-10) Hirjee, Hussein; Brown, Daniel
Imperfect and internal rhymes are two important features in rap music previously ignored in the music information retrieval literature. We developed a method of scoring potential rhymes using a probabilistic model based on phoneme frequencies in rap lyrics. We used this scoring scheme to automatically identify internal and line-final rhymes in song lyrics and demonstrated the performance of this method compared to rules-based models. We then calculated higher-level rhyme features and used them to compare rhyming styles in song lyrics from different genres, and for different rap artists. We found that these detected features corresponded to real- world descriptions of rhyming style and were strongly characteristic of different rappers, resulting in potential applications to style-based comparison, music recommendation, and authorship identification.
Editor's Note
(Empirical Musicology Review, 2010-10) Keller, Peter E.

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