FEATURE
SKYNOTE: AN EXPERT AI TEACHER Right RCM violinist Katherine Yoon using the SkyNote system
From programs that claim to curate perfect playlists to software that composes machine-made music, artificial intelligence is gaining traction in the industry. Now, a team of researchers at the Centre for Performance Science has developed a system that promises to help violinists become better, faster. Upbeat finds out more about what machine learning can do for RCM students.
The Centre for Performance Science has some good news for violinists. A team of engineers, designers and musicians has created a new technology that helps violin students build awareness of their technique, allowing them to avoid injury and acquire skills more efficiently. The intelligent learning system, SkyNote, is one of a suite of technologies developed as part of the EU-funded Technology Enhanced Learning of Musical Instrument Performance (TELMI) project, and is the culmination of three years of collaborative research undertaken alongside Pompeu Fabra University in Barcelona and the University of Genoa, as well as the companies Highskillz and SAICO Intelligence. The international team worked closely to find new ways of capturing and analysing violin performance, with the aim of providing valuable real-time feedback. ‘Expert performers have
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exceptional awareness and control of their bodies and instruments, which grants them not only the great consistency of quality professional musicians achieve, but also the confidence and freedom to be spontaneous’, explains Dr George Waddell, Research Associate in Performance Science at the Royal College of Music (RCM). ‘SkyNote helps violinists develop these skills by scrutinising their playing through the eyes of an expert teacher, one attuned to the technical aspects vital to their performance.’ The first step in creating this expert AI teacher was to find innovative detection technologies that could be used to collect a range of performance data, without interfering with playing. SkyNote tracks small markers that are attached to a violin and bow in order to unobtrusively monitor specific aspects of bowing including tilt, speed, weight, contact point,
