CSME 2020 Abstracts

Area 1 - Computer Supported Music Education

Full Papers
Paper Nr: 1

Kibo: A MIDI Controller with a Tangible User Interface for Music Education


Mattia D. Amico and Luca A. Ludovico

Abstract: This paper presents Kibo, a MIDI controller equipped with a simplified tangible user interface. Entirely made of wood, Kibo presents eight geometric extractable solids that can be used to trigger note events and to control musical parameters. In the framework of the cooperation with the Music Informatics Lab of the University of Milan, the distinctive features of the device and their applicability to the field of music education have been investigated. Kibo aims to offer intuitive interaction with music parameters and fosters the acquisition of specific skills in a non-formal learning environment. Benefits are particularly evident for specific target categories of users, including preschool and primary school children and people with both physical and cognitive special needs.

Paper Nr: 3

A Method for Learning Netytar: An Accessible Digital Musical Instrument


Nicola Davanzo and Federico Avanzini

Abstract: Accessible Digital Musical Instruments (ADMI) are increasingly raising interest within the scientific community, especially in the contexts of Sound and Music Computing and Human-Computer Interaction. In the past, Netytar has been proposed among these. Netytar is a software ADMI operated through the eyes using an eye tracker and an additional switch or sensor (e.g., a breath sensor). The instrument is dedicated to quadriplegic users: it belongs to the niche of gaze operated musical instruments, and has been proven effective and functional through testing. Although there are several other gaze operated ADMIs available in market and literature, a formal method for studying music with them has not yet been proposed. The present work introduces a simple study method based on a set of exercises. This can be useful for approaching musical performance with Netytar, but it’s also potentially generalizable for learning other similar instruments. The exercises are illustrated, discussed and explained in view of an improvement. A simple musical notation is introduced. At the end of a learning cycle, a user is expected to be able to perform simple melodies, and have a basis with which to learn other new ones. In the future, the method will be tested with the target users.

Paper Nr: 4

Performance Assessment Technologies for the Support of Musical Instrument Learning


Vsevolod Eremenko, Alia Morsi, Jyoti Narang and Xavier Serra

Abstract: Recent technological developments are having a significant impact on musical instruments and singing voice learning. A proof is the number of successful software applications that are being used by aspiring musicians in their regular practice. These practicing apps offer many useful functionalities to support learning, including performance assessment technologies that analyze the sound produced by the student while playing, identifying performance errors and giving useful feedback. However, despite the advancements in these sound analysis technologies, they are still not reliable and effective enough to support the strict requirements of a professional music education context. In this article we first introduce the topic and context, reviewing some of the work done in the practice of music assessment, then going over the current state of the art in performance assessment technologies, and presenting, as a proof of concept, a complete assessment system that we have developed for supporting guitar exercises. We conclude by identifying the challenges that should be addressed in order to further advance these assessment technologies and their useful integration into professional learning contexts.

Paper Nr: 5

Computational Music Thinking Patterns: Connecting Music Education with Computer Science Education through the Design of Interactive Notations


Alexander Repenning, Jürg Zurmühle, Anna Lamprou and Daniel Hug

Abstract: Computational Music Thinking combines computing education and music education with the goal to overcome common aptitudinal and attitudinal challenges. Many students, and teachers, believe that writing programs or performing music is beyond their natural abilities. Instead of trying to teach computing and music separately, Computational Music Thinking employs the design of interactive notations as a synergistic activity to learn simultaneously about computation and music. On the one hand, music can turn abstract computational concepts into enjoyable concrete experiences. Computation, on the other hand, can expand students’ notion of music education well beyond music performance. A course with elementary school pre-service teachers explored the teaching of Computational Music Thinking through a small set of constructs called Computational Music Thinking Patterns. These patterns are centered around educational activities to design interactive notations in accessible as well as engaging ways. Computational Music Thinking Patterns expand our previous work on Computational Thinking Patterns used in game design and simulation authoring activities. Data collected from the course suggest highly positive effects on teachers' attitudes towards believing that Computational Music Thinking is important to their teaching, that Computational Music Thinking helps the comprehension of computer science and that Computational Music Thinking helps the comprehension of music.

Short Papers
Paper Nr: 6

The CrazySquare Project: A Technological Pedagogical Content Knowledge Solution


Federica Caruso, Sara Peretti, Lara Corbacchini, Carlo Centofanti and Alessandro D’errico

Abstract: The aim of this paper is to present the current status of the CrazySquare project, a research and development project aiming at realizing an ICT support system for playing guitar within Italian middle schools. The CrazySquare project follows an iterative process based on the TEL-oriented UCD approach. Currently, we are designing the user-based evaluation of the second iteration. Differently from the first iteration, which produced a prototype aimed at digitalizing the paper and pencil CrazySquare procedure, the current iteration aims at developing an ICT learning tool including some gamification elements, such as rewards, points, levels, and immediate feedback.

Paper Nr: 7

Interactive Musical Setting with Deep Learning and Object Recognition


Mário Cardoso and Rui P. Lopes

Abstract: The SeMI - Interactive Musical Setting, explores the possibilities of joining machine learning, the physical and the sound world. In this context, a machine learning algorithm and model was used to identify physical objects through image processing. Each physical object is associated with a student’s produced musical texture that starts playing when the object is recognized by the device. This allows defining use cases in which students have to develop diverse although interrelated sound textures and combine them with a physical world, in both a fake orchestra, that reacts to people and objects in front of it, and mood rooms, for example. The application was developed for iPad and iPhone, using Swift programming language and the iOS operating system and used in the classes of the masters on Teaching of Musical Education in the Basic School.