Playing with correct intonation is one of the major challenges for a string player. A player must learn how to physically reproduce a target pitch, but before that, the player must learn what correct intonation is. This requires audiation- the aural equivalent of visualization- of every note along with self-assessment whether the pitch played matches the target, and if not, what action should be taken to correct it. A challenge for successful learning is that much of it occurs during practice, (...) typically without outside supervision. A student who has not yet learned to hear correct intonation may repeatedly practice out of tune, blithely normalising bad habits and bad intonation. The real-time reflective nature of intonation and its consistent demand on attention make it a ripe target for technological intervention. Using a violin augmented to combine fingerboard sensors with audio analysis for real-time pitch detection, we examine the efficacy of three methods of real-time feedback for improving intonation and pitch learning. The first, aural feedback in the form of an in-tune guide pitch following the student in real-time, is inspired by the tradition of students playing along with teachers. The second is visual feedback on intonation correctness using an algorithm optimised for use throughout normal practice. The third is a combination of the two methods, simultaneously providing aural and visual feedback. Twelve beginning violinists, including children and adults, were given four in-situ 20-30 minute lessons. Each lesson used one of the intonation feedback methods, along with a control lesson using no feedback. We collected data on intonation accuracy and conducted interviews on student experience and preference. The results varied by player, with evidence of some players being helped by the feedback methods but also cases where the feedback was distracting and intonation suffered. However interviews suggested a high level of interest and potential in having such tools to help during practice, and results also suggested that it takes time to learn to use the real-time aural and visual feedback. Both methods of feedback demonstrate potential for assisting self-reflection during individual practice. (shrink)

Extensive training with a musical instrument results in the automatisation of the bodily operations needed to manipulate the instrument: the performer no longer has to consciously think about the instrument while playing. The ability of the performer to automate operations on the instrument is due to sensorimotor mechanisms that can predict changes in the state of the body and the instrument in response to motor commands. But how strong are these mechanisms? To what extent can we alter the structure of (...) the instrument before they disappear? We performed an exploratory study to understand whether and how sensorimotor predictions survive instrument modification. We asked seven professional violinists to perform repertoire pieces and sight-reading exercises on four different violins: their own, a cheap violin, a small violin, and a violin whose strings had been put on in reverse order. We performed a series of quantitative investigations on performance intonation and duration, and on bowing gestures and errors. The analysis revealed that participants struggled adapting to the altered instruments, suggesting that prediction mechanisms are a function of instrument configuration. In particular, the analysis of bowing errors, intonation, and of performance duration suggested that the performance with the reverse violin was much less fluent and precise than the performer's own instrument; the performance with the small violin was also sub-standard though to a lesser extent. We also observed that violinists were differently affected by instrument modifications, suggesting that the capability to adapt to a new instrument is highly personal. (shrink)