Improvisation in interactive music systems

This project investigates machine listening and improvisation in interactive music systems with the goal of improvising musically appropriate accompaniment to an audio stream in real-time. The input audio may be from a live musical ensemble, or playback of a recording for use by a DJ. I present a collection of robust techniques for machine listening in the context of Western popular dance music genres, and strategies of improvisation to allow for intuitive and musically salient interaction in live performance. The findings are embodied in a computational agent – the Jambot – capable of real-time musical improvisation in an ensemble setting. Conceptually the agent’s functionality is split into three domains: reception, analysis and generation. The project has resulted in novel techniques for addressing a range of issues in each of these domains. In the reception domain I present a novel suite of onset detection algorithms for real-time detection and classification of percussive onsets. This suite achieves reasonable discrimination between the kick, snare and hi-hat attacks of a standard drum-kit, with sufficiently low-latency to allow perceptually simultaneous triggering of accompaniment notes. The onset detection algorithms are designed to operate in the context of complex polyphonic audio. In the analysis domain I present novel beat-tracking and metre-induction algorithms that operate in real-time and are responsive to change in a live setting. I also present a novel analytic model of rhythm, based on musically salient features. This model informs the generation process, affording intuitive parametric control and allowing for the creation of a broad range of interesting rhythms. In the generation domain I present a novel improvisatory architecture drawing on theories of music perception, which provides a mechanism for the real-time generation of complementary accompaniment in an ensemble setting. All of these innovations have been combined into a computational agent – the Jambot, which is capable of producing improvised percussive musical accompaniment to an audio stream in real-time. I situate the architectural philosophy of the Jambot within contemporary debate regarding the nature of cognition and artificial intelligence, and argue for an approach to algorithmic improvisation that privileges the minimisation of cognitive dissonance in human-computer interaction. This thesis contains extensive written discussions of the Jambot and its component algorithms, along with some comparative analyses of aspects of its operation and aesthetic evaluations of its output. The accompanying CD contains the Jambot software, along with video documentation of experiments and performances conducted during the project.

“We are not here to claim better services than any other” : Social exclusion among men from refugee backgrounds in urban and regional Australia

This paper reports on a mixed-methods study of social exclusion experiences among 233 resettled refugees living in urban and regional Queensland, Australia. The findings reported here are drawn from the SettleMEN project, a longitudinal investigation of health and settlement experiences among recently arrived adult men from refugee backgrounds conducted between 2008 and 2010. Using questionnaire surveys and semi-structured interviews, we examine four key dimensions of social exclusion: production, consumption, social relations, and services. We show that, overall, participants experienced high levels of social exclusion across all four dimensions. Participants living in regional areas were significantly more likely to be excluded from production, social relations, and services. We argue that there is a pressing need to tackle barriers to economic participation and discrimination in order to promote the social inclusion of men from refugee backgrounds.

UHT milk contains multiple forms of αS1-casein that undergo degradative changes during storage

Milk proteins are susceptible to chemical changes during processing and storage. We used proteomic tools to analyse bovine αS1-casein in UHT milk. 2-D gels of freshly processed milk αS1-casein was presented as five or more spots due to genetic polymorphism and variable phosphorylation. MS analysis after phosphopeptide enrichment allowed discrimination between phosphorylation states and genetic variants. We identified a new alternatively-spliced isoform with a deletion of exon 17, producing a new C-terminal sequence, K164SQVNSEGLHSYGL177, with a novel phosphorylation site at S174. Storage of UHT milk at elevated temperatures produced additional, more acidic αS1-casein spots on the gels and decreased the resolution of minor forms. MS analysis indicated that non-enzymatic deamidation and loss of the N-terminal dipeptide were the major contributors to the changing spot pattern. These results highlight the important role of storage temperature in the stability of milk proteins and the utility of proteomic techniques for analysis of proteins in food.

Management strategies to harness cultural diversity on Australian constructions sites : a social identity perspective

Construction sites around the world employ large numbers of people from diverse cultural backgrounds. The effective management of this cultural diversity has important implications for the productivity, safety, health and welfare of construction workers and for the performance and reputation of firms which employ them. The findings of a three year, multi-staged study of cultural diversity management practices on construction sites are critiqued using social identity theory. This reveals that so called "best-practice" diversity management strategies may have an opposite effect to that intended. It is concluded that the management of diversity on construction projects would benefit from being informed by social identity research.