Learn to Play: Computational Assessment of Musical Playability for Users' Practice

这项影响和参与的后续资金提案是基于AHRC数字转型项目的研究，“转换音乐学”（AH/L006820/1），以及琵琶音乐电子语料库项目，最近作为“开放琵琶音乐（ECOLM III）”，AH/H037829/1。它探讨了音乐的“可玩性”概念。通过开发一个系统来评估展示作品的难度，然后使用该系统根据系统判断的音乐段落创建一套练习练习，它将帮助学生学习演奏乐器（长笛、吉他或文艺复兴时期的琵琶）。吉他是当今世界上最广泛使用的乐器，互联网上提供了大量令人眼花缭乱的“标签”（以称为手谱的格式标记的乐谱），不需要正式的乐谱知识。手谱学提供了关于手指的位置来形成和弦或旋律以及它们应该演奏的顺序的说明。这是一个经得起时间考验的系统，至少从15世纪开始，已经使用了数百年，对于器乐教学尤其有用，尤其是在早期阶段。网上有大量的音乐，我们创建的系统将帮助音乐家找到适合他们技能水平的音乐。该系统将分析吉他（古典和其他风格）和文艺复兴时期鲁特琴（我们已经在ECOLM中拥有了c10,000件作品的语料库）的乐谱版本的可玩性。使用基于手伸展和位置移动的测量，我们将计算单个和弦的可玩性指数和它们之间的过渡。长笛是另一种在自学和年轻人中非常受欢迎的乐器，尤其是在学校里；根据哈克尼音乐服务的数据，我们估计仅在伦敦的学校就有超过3000名非初学者学习长笛。我们将以co-I Fiebrink对长笛音乐难度建模的早期工作为基础，这是一个非常有用的起点，因为音乐的简单纹理使我们能够专注于其旋律方面，而不是和弦（如吉他或琵琶）。然后，我们将使用标准的机器学习技术来构建可玩性模型，以识别未知长笛，吉他和琵琶作品中的困难段落。他们也将被用来对作品进行评分（基于最具技术挑战性的段落的难度），并将结果与音乐出版商在其目录中列出的分数进行比较。形成项目主要输出的概念验证演示器将使用简单的算法从这些段落中生成全新的练习，供学生练习。所有这些都将由我们的用户社区-不同级别的玩家和长笛，吉他和琵琶老师进行评估。音乐将在我们的音乐行业合作伙伴Tido music提供的高质量图形用户界面中呈现。目前用于许多教育包，主要针对业余钢琴家，它将适应与可玩性估计和练习生成后端开发和维护的远程通信。这样，我们的模型就可以从一开始就使用专业的用户界面进行测试，并使用Tido音乐库（访问限制完全在Tido的控制之下）或其他地方的乐谱，而不会损害版权所有权。吸取的教训将以两种方式直接应用。我们将为专业及业余乐手，包括参与测试的乐手，举办工作坊，与系统的设计者及开发者讨论他们对系统的评估。然后，这些反馈将被用作“创新英国”的完整提案的材料，以获得资金进行进一步的研究和开发，使这项工作从概念验证到商业上可行的产品。

This Follow-On Funding for Impact and Engagement proposal is based on research from the AHRC Digital Transformations project, 'Transforming Musicology' (AH/L006820/1), and the Electronic Corpus of Lute Music project, most recently as 'Lute Music in the Open (ECOLM III)', AH/H037829/1. It explores the concept of 'playability' of music. By developing a system to assess the difficulty of a displayed piece, and then using this system to create on demand a set of practice exercises based on passages within the music judged to be tricky by the system, it will help students learning to play an instrument (flute, guitar, or renaissance lute). The guitar is the most widespread instrument in the world today, and the internet provides a literally bewildering number of 'tabs' (scores notated in the format known as tablature) requiring no formal knowledge of music notation. Tablature provides instructions about the placement of fingers to form chords or melodies and the sequence in which they should be played. It is a system that has stood the test of time, and has been used for hundreds of years, at least since the 15th century, and is particularly useful for instrumental teaching, especially in the early stages.There is a vast amount of music available online and the system we create will help musicians find music to suit their skill level. The system will analyse the playability of tablature versions of pieces of music for guitar (classical and other styles) and for renaissance lute (we already have a corpus of c10,000 pieces in ECOLM). Using measures based on hand-stretches and position-shifts indicated in the tablature we'll compute indexes of playability of individual chords and transitions between them.The flute is another very popular instrument among self-learners and young people, especially in schools; based on figures from the Hackney Music Service, we estimate that over 3,000 non-beginner flute students take lessons in London schools alone. We'll build on earlier work carried out by co-I Fiebrink on the modelling of difficulty in flute music, a very useful starting point, since the simpler texture of the music allows us to focus on its melodic aspects rather than on chords (as on guitar or lute). We'll then use standard machine-learning techniques to build models of playability to identify difficult passages in unknown flute, guitar and lute pieces. They will also be used to grade pieces (based on the difficulty of the most technically-challenging passages) and the results compared with the grades listed by music publishers in their catalogues. The proof-of-concept demonstrator forming the main output of the project will then use simple algorithms to generate entirely new exercises derived from these passages for practising by a student.All the above will be evaluated by our user community - players at various levels and flute, guitar and lute teachers.The music will be presented within a high-quality graphical user interface provided by our music-industry partner, Tido Music. Currently used for a number of educational packages, mostly aimed at amateur pianists, it will be adapted to communicate remotely with the playability estimation and exercise generation back-end developed and maintained by Goldsmiths. This way our models can be tested from the outset with a professional user-interface, and use musical scores from the Tido music library (access restrictions entirely under Tido's control), or from elsewhere, without compromising rights ownership.The lessons learned will be applied directly in two ways. We shall hold a workshop for professional and amateur musicians, including those involved as beta-testers, to discuss their assessment of the system with its designers and developers. This feedback will then be used as material for a full proposal to Innovate UK for funds to carry out further research and development to take this work beyond proof of concept to a commercially viable product.