The 2023 Student Presentation Award winners are Nicole Cosme-Clifford (Yale University) and Ryan Galik (Michigan State University).

Cosme-Clifford and Galik headshots

The Student Presentation Award Committee is delighted to congratulate our 2023 award winners: Nicole Cosme-Clifford (Yale University) for “Play a Song from the Jukebox” and Ryan Galik (Michigan State University) for “Don't Pop the Bubble: Intersections of Ambient Music, Attention, Expectation, and Flow in Tim Hecker's Virgins.” 

Cosme-Clifford headshot

Nicole Cosme-Clifford is a PhD candidate in music theory at Yale University. She is also a consultant for the Yale Digital Humanities Lab and the Yale Graduate Writing Lab. She earned an M.A. in Music Theory from CUNY Queens College and a B.A. in Music from Stony Brook University. Her research explores explainable AI tools for music analysis; AI’s relationship to contemporary music-making; and acoustic music traditions in the United States. In the last year, she has presented papers on deep generative AI systems for music analysis, the risks and benefits of AI for music artists and songwriters, and the capabilities of large language models to learn elements of harmonic function (written in collaboration with Chris White, James Symons, and Kavi Kapoor).

Her SMT conference talk, "Play A Song From the Jukebox," focuses on an audio clip created in the style of Dolly Parton by an AI called Jukebox (OpenAI). Through analysis of the algorithm’s technical structure and musical outputs, she claims that Jukebox produces a series of sonic lenses through which we may read large collections of music recordings. Taking the generated Dolly Parton clip as one such series of lenses, she identifies vocal tendencies in Parton’s bluegrass-leaning recordings that have yet to be discussed in depth by music scholars. At the same time, she demonstrates that deep AI systems like Jukebox are inherently opaque, which makes them risky. She ultimately advocates for a diverse discourse around the benefits and risks of music-focused AI technology. 


Galik headshot

Ryan Galik is a master’s student studying music theory and composition at Michigan State University. He was previously an elementary music teacher based outside of Princeton, New Jersey and is now eagerly applying to PhD programs in music theory. His recent research investigates musical narrative embedding, cognition-informed aural skills methodologies, and twenty-first-century music broadly.

The presentation he gave at SMT’s national conference, “Don’t Pop the Bubble,” considers Tim Hecker’s 2013 album Virgins for its deviations from more traditionally ambient music. Through survey of scholarship on ambient music, attention, expectation, and flow states, he argues that the album can nevertheless be heard as ambient if listeners possess sufficient expectations with comparable music to dampen the album’s attention-demanding characteristics. More broadly, he suggests that music listening trends toward an optimal balance of dynamic expectations met and thwarted.

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