MML | Knowledge Sharing Session, March 12th: "Generative Music Model Evaluation: Metrics, Misalignments, Meanings"
Munich Music Labs
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This week we have a great presenter!
🎤 Presenter: Doctor of Musical Arts, Alexander Sigman, a composer, engineer, and musician with many years of experience working with generative music AI startups.
Earlier in his career, he was deeply involved in academia across multiple countries, including the United States (Stanford University, New York University), South Korea (Keimyung University), and Japan (International College of Liberal Arts at Yamanashi Gakuin University).
His music compositions have been commercially released on the New Focus, Carrier, and Innova labels.
🎧 You can explore some of his compositions here: https://www.lxsigman.com/
💡 What to Expect: In every article on generative AI models, there is an evaluation section. In the music domain, there is a relatively standard "Swiss army knife" of objective metrics and subjective assessments. But what do these acronyms and scores actually mean, and to what extent can they be trusted? In this presentation, Dr. Sigman will examine the insights that the most commonly used evaluation techniques shed on model performance, and their respective limitations. The design and analysis of listening tests will subsequently be discussed. After analysing these methods individually, the synthesis of objective and subjective indicators to approach a complete picture of model capabilities, as well as the application of "reinforcement learning with AI feedback" to steer the model in the direction of subjective preferences will be addressed.
📅 Date: Thursday, March 12th at 17:00 CET
📍 Location: Live on Discord, register here
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