Analyzing and Predicting Stability in Dutch Folk Songs
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Berit Janssen RETAINED OR LOST IN TRANSMISSION? Analyzing and Predicting Stability in Dutch Folk Songs Berit Janssen RETAINED OR LOST IN TRANSMISSION? Deze uitgave is mede mogelijk gemaakt door de J.E. Jurriaanse Stichting. RETAINED OR LOST IN TRANSMISSION? Analyzing and Predicting Stability in Dutch Folk Songs berit janssen ILLC Dissertation Series DS-2018-01 For further information about ILLC-publications, please contact Institute for Logic, Language and Computation Universiteit van Amsterdam Science Park 107 1098 XG Amsterdam phone: +31-20-525 6051 e-mail: [email protected] homepage: http://www.illc.uva.nl/ Copyright c 2018 by Berit Janssen. Published under the Creative Commons Attributions Licence, CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/) This document was typeset using the LaTeX template classicthesis developed by André Miede (http://code.google.com/p/classicthesis/). Cover design by Tessa Veldhorst (http://www.deschaapjesfabriek.nl/). Printed and bound by OffPage. ISBN: 978–94–6182–861–3 RETAINED OR LOST IN TRANSMISSION? Analyzing and Predicting Stability in Dutch Folk Songs Academisch Proefschrift ter verkrijging van de graad van doctor aan de Universiteit van Amsterdam op gezag van de Rector Magnificus prof. dr. ir. K.I.J. Maex ten overstaan van een door het College voor Promoties ingestelde commissie, in het openbaar te verdedigen in de Aula der Universiteit op 9 februari 2018, 13 uur door Berit Dorle Janssen geboren te Brockel, Duitsland Promotiecommisie Promotor: Prof. dr. H.J. Honing Universiteit van Amsterdam Copromotor: dr. ir. P. van Kranenburg Meertens Instituut Overige leden: Prof. dr. J.J.E. Kursell Universiteit van Amsterdam Prof. dr. L.W.M. Bod Universiteit van Amsterdam Prof. dr. T. Meder Rijksuniversiteit Groningen Dr. E. Gómez Universitat Pompeu Fabra Dr. J.A. Burgoyne Universiteit van Amsterdam Faculteit der Geesteswetenschappen The research described in this dissertation was performed at the Meertens Institute, Amsterdam, and funded by the Computational Humanities programme of the Royal Netherlands Academy of Arts and Sciences (KNAW), under the auspices of the Tunes &Tales project. I’ve been doing it for years, my goal is moving near; It says “Look I’m over here”, then it up and disappear. Some say that knowledge is something sat in your lap, Some say that knowledge is something you never have. — Kate Bush, “Sat in Your Lap” Dedicated to everyone who accompanied me on this longest journey. CONTRIBUTIONS Chapter 1, introduction Berit Janssen (BJ) wrote the Introduction and created the figures, with contributions by Henkjan Honing (HH) and Peter van Kranenburg (PvK). Theo Meder gave feedback on Section 1.1.1. Chapter 2, analyzing stability BJ wrote this chapter and created the figures, with contributions by HH and PvK. Chapter 3, musical pattern discovery This literature overview of pattern discovery is based on two publications, (Janssen, de Haas, Volk, & van Kranenburg, 2013) and (Janssen, de Haas, Volk, & van Kranen- burg, 2014). BJ performed the literature study and wrote the manuscripts, with con- tributions by Bas de Haas, PvK and Anja Volk (AV). BJ revised these publications by including the most recent literature, and modified Table 4.1, based on suggestions by Sally Wyatt and Andreas van Cranenburgh. Chapter 4, finding occurrences of melodic phrases in folk songs The first stage of this research has been presented at the 2015 International Conference of the Society for Music Information Retrieval (Janssen, van Kranenburg, & Volk, 2015). BJ designed the method, performed the analyses, created the figures and wrote the manuscript of this publication. PvK advised on the method and edited the manuscript. AV advised on the literature background and edited the manuscript. For a subsequent publication in the Journal of New Music Research (Janssen, van Kranenburg, & Volk, 2017), BJ modified the original method and evaluation, based on feedback by PvK and an anonymous reviewer. BJ created the figures and revised the manuscript, with contributions by PvK and AV. The current chapter is based on this later publication. Chapter 5, predicting stability in folk song transmission The analysis of stability has appeared in Frontiers of Psychology (Janssen, Burgoyne, & Honing, 2017). BJ performed the analyses of musical and statistical data, created the figures and wrote the manuscript. John Ashley Burgoyne advised on the statisti- cal analysis, helped with Figure 5.5, and edited the manuscript. HH advised on the vii analysis of musical data and edited the manuscript. BJ extended the chapter for the dissertation, based on feedback by PvK and HH. Chapter 6, conclusions and future work BJ wrote the Conclusion, with contributions by HH and PvK. Folgert Karsdorp gave feedback on an early draft on cultural transmission. Appendix A, the role of absolute pitch memory in the oral transmis- sion of folksongs The appendix appeared in Empirical Musicology Review (Olthof, Janssen, & Honing, 2015). Based on a research idea by HH, Merwin Olthof performed the analyses and wrote the manuscript. BJ advised on the pitch analysis and statistical evaluation, cre- ated Figure A.3 and edited the manuscript. PvK advised on the automatic pitch analy- sis. HH advised on the statistical analysis, created Figures A.1 and A.2, and edited the manuscript. CONTENTS acknowledgements 1 1introduction 3 1.1 Terminology 3 1.1.1 Musicological terminology 4 1.1.2 Computational terminology 5 1.2 Theories and studies on music transmission 5 1.2.1 Artificial transmission chains 7 1.2.2 Comparing variants in folk song collections 8 1.3 The studied material 9 1.4 Music representation 12 1.5 Outline of the dissertation 13 i quantifying stability and variation 17 2analyzingmusicalvariation 19 2.1 Musical aspects 19 2.2 Studies on musical variation with various musical aspects 21 2.2.1 Musical aspects in the comparison of musical traditions 21 2.2.2 Musical aspects for organizing European folk song collections 24 2.2.3 Musical aspects in diachronous studies 26 2.3 Research on quantifying variation of note sequences in folk songs 28 2.3.1 Units of transmission 28 2.3.2 Stability of note sequences 30 2.4 Conclusion 31 3musicalpatterndiscovery 33 3.1 Goals of musical pattern discovery 34 3.2 Pattern discovery methods 36 3.2.1 String-based, time-series and geometric methods 36 3.2.2 Exact or approximate matching 38 3.2.3 Recent developments and new challenges 39 3.3 Music representation 40 3.3.1 Recent developments and new challenges 41 3.4 Filtering 41 3.4.1 Filtering based on length 42 3.4.2 Filtering based on frequency 42 3.4.3 Filtering based on spacing 43 3.4.4 Filtering based on similarity 43 3.4.5 Recent developments and new challenges 44 3.5 Evaluation 45 3.5.1 Qualitative evaluation 45 ix x contents 3.5.2 Evaluation on speed 45 3.5.3 Evaluation on segmentation 45 3.5.4 Evaluation on classification 46 3.5.5 Evaluation on compression 46 3.5.6 Evaluation on annotated patterns 46 3.5.7 Recent developments and new challenges 47 3.6 Conclusion 48 4findingoccurrencesofmelodicsegmentsinfolksongs 51 4.1 Material 53 4.2 Compared Similarity Measures 54 4.2.1 Similarity Measures Comparing Equal-Length Note Sequences 56 4.2.2 Similarity Measures Comparing Variable-Length Note Sequences 57 4.2.3 Similarity Measures Comparing Abstract Representations 59 4.3 Evaluation 60 4.3.1 Glass ceiling 62 4.3.2 Baselines 62 4.4 Comparison of similarity measures 63 4.4.1 Results 63 4.4.2 Discussion 65 4.5 Dealing with transposition and time dilation differences 66 4.5.1 Music representations 66 4.5.2 Results 67 4.5.3 Discussion 70 4.6 Combination of the best-performing measures 71 4.6.1 Method 71 4.6.2 Results 71 4.6.3 Discussion 72 4.7 Optimization and performance of similarity measures for data subsets 72 4.7.1 Method 73 4.7.2 Similarity thresholds 73 4.7.3 Agreement with ground truth 75 4.7.4 Discussion 76 4.8 Conclusion 76 ii predicting stability 79 5predictingstabilityinfolksongtransmission 81 5.1 Hypothesized predictors for stability 81 5.1.1 Phrase length 82 5.1.2 Phrase repetition 82 5.1.3 Phrase position 82 5.1.4 Melodic expectancy 83 5.1.5 Repeating motifs 85 5.2 Material 87 contents xi 5.3 Formalizing hypotheses 87 5.3.1 Influence of phrase length 88 5.3.2 Influence of rehearsal 89 5.3.3 Influence of the primacy effect 89 5.3.4 Influence of expectancy 90 5.3.5 The influence of repeating motifs 94 5.4 Research method 97 5.4.1 Logistic regression 97 5.4.2 Generalized Linear Mixed Model 100 5.4.3 Model selection 101 5.5 Results 101 5.6 Discussion 103 6conclusionsandfuturework 107 6.1 Transmission 107 6.2 Quantifying stability and variation 109 6.3 Predicting stability 112 iii appendix 115 atheroleofabsolutepitchmemoryintheoraltransmission of folksongs 117 a.1 Background 118 a.1.1 Traditional Absolute Pitch Versus Absolute Pitch Memory 118 a.1.2 Related Work on Absolute Pitch Memory 118 a.1.3 Song Memory 119 a.1.4 Material 120 a.2 Dataset A: Between tune family analysis 121 a.2.1 Method 121 a.2.2 Quantitative analysis with circular statistics 122 a.2.3 Baseline 123 a.2.4 Results 123 a.3 Dataset B: Between and within tune family analysis 124 a.3.1 Method 124 a.3.2 Baseline 125 a.3.3 Results 125 a.4 Discussion 126 a.4.1 A Role for Absolute Pitch Memory in Oral Transmission of Folk Songs 126 a.4.2 Gender, Lyrics and Geographical Origins 129 a.5 Conclusions 130 bsimilaritymeasuresandmusicrepresentations 133 bibliography 135 glossary 149 xii contents samenvatting 157 summary 159 zusammenfassung 161 biography 163 titles in the illc dissertation series 165 ACKNOWLEDGEMENTS I needed some time to consider when I got the offer to join the Tunes & Tales project in 2011.