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Evolving Targeted Sight Reading Exercises

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Evolving Targeted Sight Reading Exercises Intelligent Tools for Deliberate Music Practice: Evolving Targeted Sight Reading Exercises Charlotte Pierce A thesis presented for the degree of Doctor of Philosophy 2019 Abstract Musical skills are generally considered to be complex and difficult to learn. Recently, efforts have been made to create digital applications for teaching these skills and enhancing or en- couraging student’s deliberate practice of them. However, existing work in this space does not take advantage of the capabilities of modern technology. Often digital tools are simply screen- based translations of existing physical materials and offer no additional or ‘smart’ functionality. The purpose of this research is to determine ways in which technology can be used to enhance existing or create new digital music teaching tools and aides. This project specifically considers the learning of musical sight reading skills. There is a significant resource constraint in this area. Sight reading is the ability to perform a piece or phrase of music without having seen it before. Therefore, as soon as an exercise has been completed it can no longer be considered a sight reading exercise. This means that the traditional approach of using expert- written practice material is ineffective, as such material is expensive to produce and limited in quantity. As deliberate practice is key to gaining competence in sight reading, this resource constraint is a large barrier for musicians seeking to develop sight reading skills. The work presented in this thesis primarily aims to consider the opportunities for de- veloping digital applications which enable user’s deliberate practice of musical sight reading. It also seeks to model an example of such an application and validate its effectiveness against existing solutions and standard practice. This application is developed with the aim of gen- erating music that, whilst being playable by a human, is aesthetically pleasing, is adaptive in difficulty, and can incorporate specific technical skills. An application with these characteristics represents a solution to overcoming the resource constraint described above. iii Acknowledgements First thanks must go to my advisors. To Dr. Clinton Woodward, thank you for encouraging my research endeavours from as far back as my undergraduate studies. You helped me prove to myself that I could be successful in this space and, more importantly, never seemed to doubt that I would produce results. Dr. Anthony Bartel, thank you for taking a chance on a random student you had just met, then accepting more responsibility than you originally signed up for. Your input has been invaluable. To Professor Tim Hendtlass, I can not thank you enough for joining my team. Jumping onto a project part way through is never easy, but from the moment you agreed to help you have consistently provided sound advice and guidance. As Clinton would say, you “really don’t know how to be retired”! To my parents, Dianne and Mark, thank you for supporting me throughout my education, not just this last part. Without you both I would not have had the resources to get to the start of a PhD, let alone finish it. I don’t think I can repay you, but I can try to do so in the form of free dog sitting and tech support. To my sisters, Marianne and Louise, thanks for pretending to be interested in my ‘nerd talk’. In your own ways you have both demonstrated to me the value in whole-heartedly work- ing towards a goal, even when it’s really, really hard. I hope I can support you both in the pursuit of your goals as you have supported me with with mine. To my friends and valued members of the “Suffer’o’wave” (and any other titles we may use in the future), you are anything but normal people. Thanks for listening to my stress rants, and always responding with appropriately funny pictures and gifs. Amy, as always you have gone above and beyond the duties of an ordinary friend, but I always knew you were extraordinary. Somehow I will get you back for that (I mean this in the nicest way possible, of course). It will probably involve fire. Finally, to James. You have been the chief pep talk giver, forgiver of grumpy moods, bringer of snacks, and executive in charge of Taking Breaks™. Thank you for being that person, and thank you for the thousands of other things, big and small, that you did to help me and support me over the past few years. I am beyond grateful for all of it. Charlotte Pierce, 2019 v Publications Arising from this Thesis Some of the work described in this thesis has been published in the following paper: Charlotte Pierce and Clinton J. Woodward. A taxonomy for describing content and ac- tivities in music education. In Proceedings of the Australian Society for Music Education (ASME) National Conference, 2017 vii Declaration I declare that this thesis contains no material that has been accepted for the award of any other degree or diploma and to the best of my knowledge contains no material previously published or written by another person except where due reference is made in the text of this thesis. Charlotte Pierce, 2019 ix Contents 1 Introduction 1 1.1 Context . 1 1.2 Research Questions . 2 1.3 Key Contributions . 3 1.4 Thesis Structure . 4 2 Background 7 2.1 Overview . 7 2.2 Challenges in Music Education . 7 2.3 Use of Technology in Music Education . 9 2.4 Musical Sight Reading . 11 2.5 Software for Learning and Practicing Musical Sight Reading . 12 2.6 Human Algorithms for Generating Music . 16 2.7 Computer Music Generation . 18 2.8 Algorithms for Computer Music Generation . 20 2.9 Evolutionary Algorithms for Computer Music Generation . 28 2.10 Summary . 30 3 A Taxonomy for Describing Musical Content and Activities 31 3.1 Overview . 31 3.1.1 Background . 32 3.1.2 Chapter Structure . 33 3.2 Content Areas . 35 3.2.1 Overview . 35 3.2.2 Reading . 35 3.2.3 Rhythm . 35 3.2.4 Scales . 38 3.2.5 Elements of Harmony . 38 3.2.6 Harmonic Structures . 41 3.2.7 Style . 41 3.2.8 Instrument-Specific . 44 3.2.9 Historical and General Knowledge . 44 3.3 Activities . 47 3.3.1 Overview . 47 3.3.2 Recognition Activities . 48 3.3.2.1 Overview . 48 xi CONTENTS 3.3.2.2 Auditory Recognition Activities . 48 3.3.2.3 Visual Recognition Activities . 50 3.3.3 Description Activities . 50 3.3.3.1 Overview . 50 3.3.3.2 Auditory Description Activities . 50 3.3.3.3 Visual Description Activities . 53 3.3.4 Playback Activities . 53 3.3.4.1 Overview . 53 3.3.4.2 Visual Playback Activities . 53 3.3.4.3 Memory Playback Activities . 56 3.3.5 Notation Activities . 57 3.4 Discussion . 58 3.5 Summary . 59 4 Taxonomy Validation: Music Aptitude Tests 61 4.1 Overview . 61 4.2 Mapping Tests to Taxonomy . 61 4.2.1 Overview . 61 4.2.2 Seashore’s Measures of Musical Talents . 61 4.2.3 Revesz’s Tests of Musical Ability . 62 4.2.4 Kwalwasser’s Tests and Measurements in Music . 62 4.2.4.1 Overview . 62 4.2.4.2 Kwalwasser-Ruch Test of Musical Accomplishment . 63 4.2.4.3 Kwalwasser Test of Music Appreciation . 63 4.2.4.4 Kwalwasser-Dykema (K-D) Musical Talent Tests . 64 4.2.4.5 Kwalwasser’s Music Talent Test . 65 4.2.5 Schoen’s Tests of Musical Feeling and Understanding . 65 4.2.6 Torgerson-Fahnestock Tests . 65 4.2.7 Drake Musical Aptitude Tests . 67 4.2.8 Gordon’s Aptitude Tests . 67 4.2.8.1 Overview . 67 4.2.8.2 Gordon’s Musical Aptitude Profile (MAP) . 67 4.2.8.3 Gordon’s Measures of Music Audiation . 68 4.2.9 Bentley’s Measures of Musical Abilities . 68 4.2.10 Wing’s Tests of Musical Ability and Appreciation . 69 4.2.11 Iowa Tests of Music Literacy . 69 4.2.12 Colwell Music Achievement Test . 70 4.2.13 Karma’s Test of Structure Ability . 70 4.2.14 Musical Aptitude Indicator . 70 4.2.15 The Profile of Music Perception Skills (PROMS) . 70 4.3 Results . 72 4.3.1 Activity Types . 72 4.3.2 Content Areas . 75 4.3.3 Subtest Equivalence . 79 xii CONTENTS 4.3.3.1 Overview . 79 4.3.3.2 Auditory Description Activities of Reading Content . 79 4.3.3.3 Auditory Description Activities of Rhythm Content . 80 4.3.3.4 Auditory Description Activities of Scales Content . 80 4.3.3.5 Auditory Description Activities of Elements of Harmony Content 80 4.3.3.6 Auditory Description Activities of Harmonic Structures Content . 80 4.3.3.7 Auditory Description Activities of Style Content . 83 4.3.3.8 Auditory Description of Historical of General Knowledge Content 83 4.3.3.9 Visual Description Activities of Reading Content . 83 4.3.3.10 Visual Description Activities of Rhythm Content . 83 4.3.3.11 Memory Playback Activities of Rhythm Only . 86 4.4 Discussion . 86 4.5 Summary . 90 5 iOS Music Teaching Applications: State of the Art 91 5.1 Overview . 91 5.2 Method . 91 5.2.1 Overview . ..
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