The purpose of this project was to develop computer programs for use in a hybrid system for electronic music synthesis. The system consists of a D17B Minuteman computer and an Arp 2500 synthesizer. The programs enable a user to create control signals with the D17B for use in any Arp patch.Up to 511 distinct voltage events may be specified. A voltage event is defined as a discrete voltage or as a continuous (ramp) voltage during a specified duration period. A discrete voltage remains constant over the duration. A continuous voltage changes linearly over the duration period. A voltage event is defined in the range of 0 to +10 Volts. An event duration is defined in the range of zero to thirty seconds in any increment of one-tenth of a second.The project was achieved in three steps. First, the user inputs data to the D17B memory describing the voltage events. Next, a program is executed to convert the data to a form usable by the computer. Third, a program is executed which outputs two control signals. One control signal outputs the voltage event; it is used with any voltage-controlled device on the Arp. A pulse signal is output for each voltage event; it is used as a gate for an envelope generator.This hybrid system expands the capabilities of the Arp. It may be used in place of the Arp sequencer to create longer sequences of control signals. The programs give the user exact control over the voltage value and duration of each voltage event. / School of Music

THE USE OF COMPUTERS IN MUSIC EDUCATION IN SOUTH WEST AFRICA ZOHOVj Ashley Mark, M. Mus. University of the Witwatersrand, Johannesburg, 1986. This study compared CAT with conventional group-class Instruction to determine the degree of skill proficiency in interval and rhythm dictation obtained by students exposed to the alternate forms of instruction. Forty-three students attending the Windhoek Conservatoire, aged between eleven and fifteen years, volunteered to participate, A modified pre-test/post-test control group design was used. A researcher-built pre-test was administered and students were matched according to interval scores and grade level. Each pair was then randomly assigned to either the experimental (GAI) or the control (teacher) group: Intervals. An inverse assignment of these intact groups was made. The control group now became an experimental group (CAT: Rhythms), while the pre-defined experimental group was treated as its control (teacher: Rhythms), Each student received CAT and group-class instruction for two half-hour sessions per week for six months (14-18 hours of instruction), GAI was administered using the Micro GUIDO Ear Training System, specially adapted by the researcher to suit study at a grade level. Results of the non-parametric tests indicated no difference between E and G groups (p » ,05). Results favouring the E group in interval recognition were obtained (p = ,10). Further, the C group showed a greater proficiency in ability to notate rhythms correctly (p - , 10). No differences were observed in a comparison of sex, age and degree of theory knowledge among students receiving GAI (p " >05), A positive response by students to GAI was Indicated in an attitudinal questionnaire, It was concluded that CAI served as a feasible alternative to conventional instruction but that optimum benefits would be derived if used as an adjunct to conventional instruction.

published_or_final_version / Computer Science and Information Systems / Doctoral / Doctor of Philosophy

Automatic music genre classi cation is a high-level task in the eld of Music Information Retrieval (MIR). It refers to the process of automatically assigning genre labels to music for various tasks, including, but not limited to categorization, organization and browsing. This is a topic which has seen an increase in interest recently as one of the cornerstones of MIR. However, due to the subjective and ambiguous nature of music, traditional single-label classi cation is inadequate. In this thesis, we study multi-label music genre classi cation from perceptual and computational perspectives. First, we design a set of perceptual experiments to investigate the genre-labelling behavior of individuals. The results from these experiments lead us to speculate that multi-label classi cation is more appropriate for classifying music genres. Second, we design a set of computational experiments to evaluate multi-label classi cation algorithms on music. These experiments not only support our speculation but also reveal which algorithms are more suitable for music genre classi cation. Finally, we propose and examine a group of ensemble approaches for combining multi-label classi cation algorithms to further improve classi cation performance. ii / viii, 87 leaves ; 29 cm

Modelling a listener's perception of musical rhythm requires both an understanding of rhythm as a whole as well as a definition of its constituent elements. The hypothesis is that once we can adequately define rhythm, we can then begin to design and implement models to gain insight into the perceptual processes which occur when listening to rhythmic sequences. This research outlines studies which have attempted to define and outline both the structure and the perception of rhythm. Based on the conclusions of these investigations, a computer model is designed and implemented using connectionist techniques. The emphases on this model are to arrive at a viable solution for extracting rhythmic material from performed input, and to implement time-scale invariance. Time-scale invariance allows the system to recognize (categorize) similar patterns played at different tempos as being the same pattern. The performance of this model is evaluated against earlier models designed with similar neural network architectures as well as in relation to the conclusions drawn by music theorists and psychologists.

The computer classification of musical audio can form the basis for systems that allow new ways of interacting with digital music collections. Existing music classification systems suffer, however, from inaccuracy as well as poor scalability. Feature selection is a machine-learning tool that can potentially improve both accuracy and scalability of classification. Unfortunately, there is no consensus on which feature selection algorithms are most appropriate or on how to evaluate the effectiveness of feature selection. Based on relevant literature in music information retrieval (MIR) and machine learning and on empirical testing, the thesis specifies an appropriate evaluation method for feature selection, employs this method to compare existing feature selection algorithms, and evaluates an appropriate feature selection algorithm on the problem of musical genre classification. The outcomes include an increased understanding of the potential for feature selection to benefit MIR and a new technique for optimizing one type of classification-based system.

The wide range of options for experimentation with the synthesis of sound are usually expensive, difficult to obtain, or limit the experimenter. The work described in this thesis shows how the IBM PC and software can be combined to provide a suitable platform for experimentation with different synthesis techniques. This platform is based on the PC, the Musical Instrument Digital Interface (MIDI) and a musical instrument called a digital sampler. The fundamental concepts of sound are described, with reference to digital sound reproduction. A number of synthesis techniques are described. These are evaluated according to the criteria of generality, efficiency and control. The techniques discussed are additive synthesis, frequency modulation synthesis, subtractive synthesis, granular synthesis, resynthesis, wavetable synthesis, and sampling. Spiral synthesis, physical modelling, waveshaping and spectral interpolation are discussed briefly. The Musical Instrument Digital Interface is a standard method of connecting digital musical instruments together. It is the MIDI standard and equipment conforming to that standard that makes this implementation of synthesis techniques possible. As a demonstration of the PC platform, additive synthesis, frequency modulation synthesis, granular synthesis and spiral synthesis have been implemented in software. A PC equipped with a MIDI interface card is used to perform the synthesis. The MIDI protocol is used to transmit the resultant sound to a digital sampler. The INMOS transputer is used as an accelerator, as the calculation of a waveform using software is a computational intensive process. It is concluded that sound synthesis can be performed successfully using a PC and the appropriate software, and utilizing the facilities provided by a MIDI environment including a digital sampler.

The requirement for multi-channel surround sound in audio production applications is growing rapidly. Audio processing in these applications can be costly, particularly in multi-channel systems. A distributed approach is proposed for the development of a realtime spatialization system for surround sound music production, using Ambisonic surround sound methods. The latency in the system is analyzed, with a focus on the audio processing and network delays, in order to ascertain the feasibility of an enhanced, distributed real-time spatialization system.

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