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The KnowledgeBank at OSU (76.400 recursos)

Knowledge Bank contains collections of presentations, publications and reports related to Ohio State University.

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

Mostrando recursos 1 - 7 de 7

  1. Announcements

    Keller, Peter E.
    Calls for Papers, Conferences, Podcasts

  2. Third International Conference of Students of Systematic Musicology (SysMus10): A Conference Report

    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...

  3. Hooked on Music Information Retrieval

    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...

  4. Time Series Analysis as a Method to Examine Acoustical Influences on Real-time Perception of Music

    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...

  5. Lure(d) into listening: The potential of cognition-based music information retrieval

    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...

  6. Using Automated Rhyme Detection to Characterize Rhyming Style in Rap Music

    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...

  7. Editor's Note

    Keller, Peter E.

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