Callaway Centre Research Seminar

Callaway Centre Research Seminar Series

The Conservatorium of Music is a vibrant centre for research in music and music education, where a thriving community of scholars is engaged in exploring the frontiers of knowledge, working on a wide range of research projects with diverse outputs.

Our free weekly seminar series showcases presenters from within UWA and from the wider community.

Alex Allen

Contrary States: Dialectical Aesthetics in William Blake and Jacob Ter Veldhuis’ The Garden of Love

Contemporary Dutch composer Jacob Ter Veldhuis’ work The Garden of Love for oboe and soundtrack (2002) recontextualises William Blake’s poem of the same name from his Songs of Innocence and Experience (1789-1794). The work juxtaposes two disparate aesthetics, here considered as the ‘divine’ and ‘earthly’, which can be seen to represent Ter Veldhuis’ style at large. Ter Veldhuis harnesses these contrasting aesthetics in The Garden of Love to depict Blake’s antithetical allegory for the conflict between individual spirituality and organised religion. I suggest that Blake’s dialectics can be used as a lens through which we can understand Ter Veldhuis’ eclectic style, which has so far resisted definition due to its disparate and contrary basis. Through the interplay of his disparate aesthetics in The Garden of Love, Ter Veldhuis embodies Blakean dialectical philosophy threefold: he represents contraries as co-substantiating equals, asserts the inherent dualism of contraries, and denounces moral judgements that engender negation

Bio

Alexandra is an honours student completing her studies in oboe performance at the UWA Conservatorium.

Jet Kye Chong

Predicting marimba stickings with neural networks

In marimba music, ‘stickings’ are the choices of mallets used to strike each note, and they significantly influence both the physical facility and expressive quality with which the music may be played. Choosing ‘good’ stickings and evaluating one’s stickings are necessary steps in learning music, but they can be slow and difficult tasks, often relying on trial-and-error vaguely guided by past experience. This is the ‘sticking problem’, which can impede technical and musical development, and hinder the learning of music. In this study, a machine learning approach is employed to address the sticking problem by predicting and annotating stickings in 4-mallet marimba music as suggestions for marimbists.

A 32,000-sample dataset is constructed from exercises in Leigh Howard Stevens’ Method of Movement for Marimba by digitally transcribing the pitch and duration data of notes in each exercise, then iterating through keys, ranges on the instrument, and valid sticking annotations. Long Short-Term Memory (LSTM) neural networks are constructed and fit to this dataset over a range of hyperparameters. K-Fold cross validation and qualitative testing are conducted on the models, yielding a maximum quantitative accuracy 77.99% (±0.32%) from a bidirectional sigmoid-activation LSTM model, and a maximum qualitative accuracy of 63% consistent across models. The discrepancies between quantitative and qualitative metrics are discussed, but promising results invite further development and study in this fiel

Bio

Jet Kye Chong is an emerging Australian composer and percussionist completing a Bachelor of Philosophy (Hons.) majoring in Mathematics and Music.

Free entry - join via Zoom (Meeting ID: 312 470 079) or click HERE

Contact details: [email protected]