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Interdisciplinary Science Reviews | 2009

Modelling Folksong Melodies

Frans Wiering; Remco C. Veltkamp; Jörg Garbers; Anja Volk; Peter van Kranenburg; L.P. Grijp

Abstract In the second half of the twentieth century, ethnomusicologists assembled a collection of more than 7000 field recordings of Dutch ballads. Collectively known as Onder de groene linde, these recordings are preserved at the Meertens Institute in Amsterdam. Because of its size, composition and quality of metadata, Onder de groene linde is a unique resource for studying the musical properties of folksongs. For such study, it would be essential to search and order the songs automatically, not just using the metadata, but especially their musical content. It is the aim of the WITCHCRAFT project to design and implement methods for processing the musical content of the songs. Such a project involves two disciplines, musicology and computer science, that have different goals and methodologies. Such differences can lead to unproductive tensions, but can also be exploited in order to attain new insights that could not have been attained by the separate disciplines.


Proceedings of the First International Conference of the SocieTY for Mathematics and Computation in Music | 2007

On Pitch and Chord Stability in Folk Song Variation Retrieval

Jörg Garbers; Anja Volk; Peter van Kranenburg; Frans Wiering; L.P. Grijp; Remco C. Veltkamp

In this paper we develop methods for computer aided folk song variation research. We examine notions and examples of stability for pitches and implied chords for a group of melodic variants. To do this we employ metrical accent levels, simple alignment techniques and visualization techniques. We explore how one can use insight into stability of a known set of variants to query for additional variants.


First International Conference of the Society of Mathematics and Computation in Music | 2007

Comparing Computational Approaches to Rhythmic and Melodic Similarity in Folksong Research

Anja Volk; Jörg Garbers; Peter van Kranenburg; Frans Wiering; L.P. Grijp; Remco C. Veltkamp

In this paper we compare computational approaches to rhythmic and melodic similarity in order to find relevant features characterizing similarity in a large collection of Dutch folksongs. Similarity rankings based on Transportation Distances are compared to an approach of rhythmic similarity based on Inner Metric Analysis proposed in this paper. The comparison between the two models demonstrates the important impact of rhythmic organization on melodic similarity.


Journal of Interdisciplinary Music Studies | 2009

Collaboration Perspectives for Folk Song Research and Music Information Retrieval: The Indispensable Role of Computational Musicology

Peter van Kranenburg; Jörg Garbers; Anja Volk; Frans Wiering; L.P. Grijp; Remco C. Veltkamp


international symposium/conference on music information retrieval | 2008

A manual annotation method for melodic similarity and the study of melody feature sets

Anja Volk; Peter van Kranenburg; Jörg Garbers; Frans Wiering; Remco C. Veltkamp; L.P. Grijp


international symposium/conference on music information retrieval | 2007

Applying Rhythmic Similarity Based on Innner Metric Analysis to Folksong Research

Anja Volk; Jörg Garbers; P. van Kranenburg; Frans Wiering; Remco C. Veltkamp; L.P. Grijp; S. Dixon; D. Bainbridge; Rainer Typke


international symposium/conference on music information retrieval | 2007

Towards Integration of MIR and Folk Song Research

P. van Kranenburg; Jörg Garbers; Anja Volk; Frans Wiering; L.P. Grijp; Remco C. Veltkamp; S. Dixon; D. Bainbridge; Rainer Typke


Meertens Online Reports | 2014

The Meertens Tune Collections

P. van Kranenburg; M.J. de Bruin; L.P. Grijp; F. Wiering


international symposium/conference on music information retrieval | 2007

USING PITCH STABILITY AMONG A GROUP OF ALIGNED QUERY MELODIES TO RETRIEVE UNIDENTIFIED VARIANT MELODIES

Peter van Kranenburg; Anja Volk; Frans Wiering; Remco C. Veltkamp; L.P. Grijp


Archive | 2008

The Study of Melodic Similarity using Manual Annotation and Melody Feature Sets

Anja Volk; Peter van Kranenburg; Frans Wiering; Remco C. Veltkamp; L.P. Grijp

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P. van Kranenburg

Royal Netherlands Academy of Arts and Sciences

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F. Wiering

Austrian Research Institute for Artificial Intelligence

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J.B. Oosterman

Radboud University Nijmegen

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