Methodologies for Music Understanding and Generation in the Context of Trustworthy AI

Explore methodologies for music understanding and generation through the lens of trustworthy AI in this plenary conference talk delivered at JSALT 2025. Discover how the Music Technology Group at Universitat Pompeu Fabra approaches computational music challenges by combining powerful machine learning techniques with domain-aware, transparent, and ethically grounded methodologies. Learn about cutting-edge research at the intersection of music and artificial intelligence, including audio analysis, symbolic music processing, generative modeling, and multimodal representation learning. Examine how principles of trustworthy AI—including fairness, transparency, cultural awareness, and reproducibility—are integrated across the research pipeline. Gain insights through examples from recent projects that demonstrate the importance of interdisciplinary collaboration and open science practices in advancing socially responsible music AI research. Understand how technical choices can reflect broader values when working with creative, subjective, and culturally diverse domains like music, and engage with discussions on balancing innovation with accountability in music AI development.