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Many music composition algorithms attempt to compose music in a particular style. The resulting music is often impressive and indistinguishable from the style of the training data, but it tends to lack significant innovation. In an effort to increase innovation in the selection of pitches and rhythms, we present a system that discovers musical motifs by coupling machine learning techniques with an inspirational component. The inspirational component allows for the discovery of musical motifs that are unlikely to be produced by a generative model, while the machine learning component harnesses innovation. Candidate motifs are extracted from non-musical media such as images and audio. Machine learning algorithms select the motifs that best comply with patterns learned from training data. This process is validated by extracting motifs from real music scores, identifying themes in the piece according to a theme database, and measuring the probability of discovering thematic motifs verses non-thematic motifs. We examine the information content of the discovered motifs by comparing the entropy of the discovered motifs, candidate motifs, and training data. We measure innovation by comparing the probability of the training data and the probability of the discovered motifs given the model. We also compare the probabilities of media-inspired motifs with random motifs and find that media inspiration is more efficient than random generation.

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The aim of this thesis is to explore the relationship between place, identity and musical practice. The study is inspired by Malta’s history and culture. This work presents a portfolio of seven musical compositions with a written component that highlights the historical and socio-cultural issues that had a bearing on the works presented. A case study of the Maltese composer Charles Camilleri is also provided. Camilleri is both a great example of a composer for whom the articulation of national identity was a primary concern and a constant source of inspiration for the author of this thesis. The pieces presented here comprise compositions for chamber ensemble, works for orchestra and two electroacoustic pieces. These works were part of projects translated into performances and artistic installations. All of them have been carried out over the past six years and the majority have been developed through synergetic collaboration with other artists. The majority of the compositions have direct links with Maltese culture and the important events in its history. All the works presented in the portfolio are bound in separate volumes and reference is made to them in the critical commentary within the body of the thesis. A number of CDs and DVDs accompany this document with recordings and MIDI files of the selected compositions.

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The dissertation is recorded computer music. It has a duration of fourteen minutes and fifty seven seconds. The source sound material is a reading of a sonnet of the same name by thirteenth century Sienese poet Cecco Angiolieri. It utilizes Linear Predictive Coding and Short-time-fourier synthesis in addition to postprocessing by spatialization and digital filtering. The discussion of the piece includes an explanation of the synthesis techniques, the pitch manipulation algorithms and the programs written by the composer to generate computer scores based on these algorithms, and finally how the individual musical events were generated and mixed together. The computer scores and programs used to generated these scores are provided after the discussion.

Night of Glass is for chamber orchestra with an estimated performance time of 14 minutes. The instrumentation for the work, using one player per part, is Flute (also small glass wind chimes), Oboe (also 1 tuned water crystal), Clarinet in A (also small glass wind chimes), Bassoon (also 1 tuned water crystal), Horn in F (also 1 tuned water crystal), Trumpet in C (also 2 tuned water crystals), Percussion (Vibraphone, Glockenspiel, Chimes, Bell Tree, Hammered Dulcimer, 3 Suspended Cymbals, 1 Large Tam-tam, 4 Roto Toms, 3 Tympani), Piano, 1st Violin, 2nd Violin, Viola, Cello, and Double Bass, While not programmatic, the work is divided into six sections each expressing a predetermined emotional content: fragility, anxiety, solitude, fear, catharsis, and reconciliation. All are emotional contents which are found in the dream-state that is reflected in the work's title. All aspects of Night of Glass (i.e., pitch material, form structure, and structural density) are centered around the unifying factor of emotional projection within each section. The work seeks emotional content through the expansion of composition procedures while being accessible to listeners.