Constraint and creative decision making in the composition of concert works, film and video-game soundtracks

This PhD research investigates the types, implications and origins of constraint within the contexts of various music composition projects. It then presents the practical value of this deeper understanding as a contemporary music composer.To explore the topic of constraint, the doctorate contains a portfolio of original music compositions and a reflective commentary on those compositions. The music spans a wide range of purposes, including works for concert hall, film and videogame. This breadth, across 33 musical works for 17 different projects of both collaborative and independent types, facilitates the extension of our understanding of constraint and its role in the process of music-making. The commentary, focussing on each composition individually or in small groups, extrapolates how constraint emerges within different circumstances.Analysing the music, in tandem with an account of their contextual backgrounds, demonstrates how different constraints influence music composition. The result of this research is that one can start to generalise the creative challenges a contemporary composer faces in the form of constraint. The research does this by proposing a series of labels: intrinsic, extrinsic, functional and aesthetic. These categories emerged through the creative practices of the portfolio, delineating and searching for constraint as a means of grounding creative decisions. The commentary and portfolio, taken together, will offer insights into the four proposed categories of constraint while explicating my compositional practice

FIELD, Issue 89, Fall 2013

https://digitalcommons.oberlin.edu/field/1094/thumbnail.jp

Sequential decision making in artificial musical intelligence

Over the past 60 years, artificial intelligence has grown from a largely academic field of research to a ubiquitous array of tools and approaches used in everyday technology. Despite its many recent successes and growing prevalence, certain meaningful facets of computational intelligence have not been as thoroughly explored. Such additional facets cover a wide array of complex mental tasks which humans carry out easily, yet are difficult for computers to mimic. A prime example of a domain in which human intelligence thrives, but machine understanding is still fairly limited, is music. Over the last decade, many researchers have applied computational tools to carry out tasks such as genre identification, music summarization, music database querying, and melodic segmentation. While these are all useful algorithmic solutions, we are still a long way from constructing complete music agents, able to mimic (at least partially) the complexity with which humans approach music. One key aspect which hasn't been sufficiently studied is that of sequential decision making in musical intelligence. This thesis strives to answer the following question: Can a sequential decision making perspective guide us in the creation of better music agents, and social agents in general? And if so, how? More specifically, this thesis focuses on two aspects of musical intelligence: music recommendation and human-agent (and more generally agent-agent) interaction in the context of music. The key contributions of this thesis are the design of better music playlist recommendation algorithms; the design of algorithms for tracking user preferences over time; new approaches for modeling people's behavior in situations that involve music; and the design of agents capable of meaningful interaction with humans and other agents in a setting where music plays a roll (either directly or indirectly). Though motivated primarily by music-related tasks, and focusing largely on people's musical preferences, this thesis also establishes that insights from music-specific case studies can also be applicable in other concrete social domains, such as different types of content recommendation. Showing the generality of insights from musical data in other contexts serves as evidence for the utility of music domains as testbeds for the development of general artificial intelligence techniques. Ultimately, this thesis demonstrates the overall usefulness of taking a sequential decision making approach in settings previously unexplored from this perspectiveComputer Science

ARAB MUSICIANS IN WASHINGTON, D.C. AREA: ETHNICITY AND IDENTITY

Musicians living in the Arab Diaspora around the Washington, D.C. metro area are a small group of multi-faceted individuals with significant contributions and intentions to propagate and disseminate their music. Various levels of identity are discussed and analyzed, including self-identity, group/ collective identity, and Arab ethnic identity. The performance and negotiation of Arab ethnic identity is apparent in selected repertoire, instrumentation, musical style, technique and expression, shared conversations about music, worldview on Arabic music and its future. For some musicians, further evidence of self-construction of one's ethnic identity entails choice of name, costume, and venue. Research completed is based on fieldwork, observations, participant-observations, interviews, and communications by phone and email. This thesis introduces concepts of Arabic music, discusses recent literature, reveals findings from case studies on individual Arab musicians and venues, and analyzes Arab identity and ethnicity in relation to particular definitions of identity found in anthropological and ethnomusicological writings. Musical lyrics, translations, transcriptions, quotes, discussions, analyses, as well as charts and diagrams of self-identity analyses are provided as evidence of the performance and negotiation of Arab identity

Red Tide, Vol. 1, No. 4 (November 4, 1971)

https://digitalcommons.bard.edu/red_tide/1003/thumbnail.jp