To obtain a sampling of expertise from the music field, the author approached the University of York’s Music Department, Music Technology Department and Music Society. Response was enthusiastic and positive in all respects, with no shortage of interested parties. Following specially-arranged demonstrations of the MIVI application, their response was as follows:

1. Prof. P. Main, Dept. of Physics, University of York

Lecturer and Researcher in the ‘Physics of Music’ and Flautist

2. Dr. A. Hunt, Dept. of Music Technology, University of York

Lecturer in ‘Electronic Musical Instruments’ and ‘Multiple Media Techniques’

From a technical standpoint, researchers in the field of music technology were impressed at the level of integration between MIVI and the VST host environment – concurring that its selection as platform was a well-informed choice. The successful importing of external dependencies such as OpenGL into the environment also fascinated them. They also believed that porting to other OS’s should be a relatively trouble-free affair.

   Furthermore, the principal methods and algorithms of the code (such as fingering, and instrument definitions) met with their approval as well. They were surprised to see the almost direct translation of finger maps (code ref. 45) from the illustrations of Boehm’s book [5].

   Both agreed that the extension to a flute model, in addition to the piano, reflected well upon the architecture. More specifically, Dr. Hunt conjectured that the system presented an excellent platform to qualitatively study the failings of the MIDI specification, whilst also implicitly identifying the necessary extensions. In this capacity, he mentioned a desire to see the MIVI system extended to encapsulate a full complement of GM instruments, though he conceded that sound effects, such as helicopters (voice #126) would only add to completeness, rather than practicality.

Again, both scholars agreed that the project posed the interesting question of how to represent breath pressure and lip shape – important aspects of wind instrument performance.

   From a music technology point of view, both were sceptical of the software’s application in an educational role. Prof. Main, in his capacity as a flautist, stated that the erudition of flute fingerings came more intuitively from knowledge of hand configuration rather than finger placement. Although iterating, with reason, that this was his own conviction, this opinion recurs in the feedback of the next section. The concept, however, inspired him to picture a physical flute interface – similar to a MIDI flute – where the computer automatically depressed the keys, as with our model. In this situation, the aspirant flautist could simply rest their fingers upon the generic flute finger locations, and allow the computer to move the keys – and, by transitivity, the hands – into the appropriate configuration. It relies on the unchanging position of fingers on the flute and, thus, it remains to be seen if such a device is permissible for other woodwind instruments, such as the oboe and clarinet.

   As pianists, Dr. Hunt and the author identified several problems with the piano tutoring system and solutions that would address them. Principally, the system, in its current state, discouraged the use of the score – Dr. Hunt felt that due to the inflexible timing of the instructions, angst over the appearance of the next note request (shaded green) led to discomfort, and an inability to relax in the environment, requiring constant attention on the graphical model. He stated that he felt ‘separated’ from hands.

   We agreed two solutions that would solve this problem. Firstly, the playback timing could be controlled through user response – a delay, pending note activation, before playback continuation, or simply an inverse connection of tempo to error count (the more frequent the errors, the lower the tempo, the easier the recital). Secondly, the introduction of a visual lookahead device, where future notes gradually ‘fade’ into focus before being required, possibly, turning green to signify their activation. This would give the learner time to prepare for shifts, etc. and also allow them to choose more optimal fingerings.

   On a similar line, Dr. Hunt, feeling that the system was too note oriented said, "I don’t feel like I’m learning music – more like it’s a hand-eye coordination test." Instead of a note-by-note approach, he advocated the introduction of phrase learning, where a bar or phrase was played back by the host, and then echoed by the student.

1. Edwina Smith, through the Dept. of Music, University of York

Flute teacher and pianist

2. Susan Franks, through the Dept. of Music, University of York / Leeds

Flute teacher (interview conducted over the phone)

3. Oliver Hancock, Dept. of Music, University of York

Student of Music, piano teacher and blues pianist

4. Chris Bluemel, Dept. of Music, University of York

Student of Music and pianist

5. Jennie Wrigley, Dept. of Music, University of York

Student of Music and flautist

From the consumer point of view, all parties were impressed with the concept of the application. Sadly, Ms. Franks’ schedule did not permit a private demonstration of the technology. Others, however, were astounded at the quality, accuracy and detail of the graphical models.

On the subject of alternative and optimal fingerings, she noted that many were only a requirement of advanced play, and that most beginners are initially taught only a default fingering for each note. She agreed that the ability to toggle this feature would be of benefit to the beginning flautist.

   Both flute teachers echoed Prof. Main’s conviction that knowledge of hand configuration is preferable to finger combination, and agreed that the addition of 3D hands and fingers to the model would drastically aid the learning process. During the demonstration, however, Ms. Smith conceded that our current implementation still proved more attractive than the traditional flute fingering tables of tuition books [5][33].

   Oliver Hancock stated that hands would be of use in the piano instrument as well. As a teacher of piano with many younger students, he said that one of the problems he faced was encouraging students away from the solitary use of their forefinger. He also thought that placing the students in a room with a MIVI system would show and guide them through this early playing obstacle, and was of considerable advantage where students are abundant and teachers at a premium.

   In contrast to Dr. Hunt’s view (see section 6.1.1), he said that the direction of the user’s gaze upon the screen was actually of advantage, compared to the fixation on the user’s keys and hands. Indeed, when play becomes competent, the performers gaze should rest on the score, which is also separate from the keyboard, and that the ‘separation’ from hands is a necessary step to proficiency.

   Also in contrast to Hunt, Hancock appreciated the rigidity of the tempo, citing examples of young students, when they use the score, incrementally stepping from note to note without due consideration of their lengths. He feels the feature would give learners an understanding of rhythm, though conceded that this would be of less use to early learners. In the latter case, he concurs with Hunt that the provision of phrase repetition would be a good introduction.