This thesis presents a complete hardware and software system to support the learning process associated with the Great Highland Bagpipe (GHB). A digital bagpipe chanter interface has been developed to enable accurate measurement of the player's nger movements and bag pressure technique, allowing detailed performance data to be captured and analysed using the software components of the system. To address the challenge of learning the diverse array of ornamentation techniques that are a central aspect of Highland piping, a novel algorithm is presented for the recognition and evaluation of a wide range of embellishments performed using the digital chanter. This allows feedback on the player's execution of the ornaments to be generated. The ornament detection facility is also shown to be e ective for automatic transcription of bagpipe notation, and for performance scoring against a ground truth recording in a game interface, Bagpipe Hero. A graphical user interface (GUI) program provides facilities for visualisation, playback and comparison of multiple performances, and for automatic detection and description of piping-speci c ngering and ornamentation errors. The development of the GUI was informed by feedback from expert pipers and a small-scale user study with students. The complete system was tested in a series of studies examining both lesson and solo practice situations. A detailed analysis of these sessions was conducted, and a range of usage patterns was observed in terms of how the system contributed to the di erent learning environments. This work is an example of a digital interface designed to connect to a long established and highly formalised musical style. Through careful consideration of the speci c challenges faced in teaching and learning the bagpipes, this thesis demonstrates how digital technologies can provide a meaningful contribution to even the most conservative cultural traditions.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:674913 |
| Date | January 2015 |
| Creators | Menzies, Duncan |
| Publisher | Queen Mary, University of London |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://qmro.qmul.ac.uk/xmlui/handle/123456789/9551 |
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