Simon Schwär, M.Sc.

I'm a PhD student in the Music Processing group, where we study how computers can help us understand music and musical signals. I currently focus on musically meaningful methods to include physical and perceptual models in frameworks for gradient-based optimization. This can be useful for many tasks in the field of music information retrieval, like the analysis and adaptation of intonation and tuning.

Even less information about me can be found on my personal website.

Topics

  • Differentiable Digital Signal Processing
  • Singing Voice and Musical Instrument Intonation

CV

Teaching

Supervised Master Theses

  • Rithika Cariappa (2024): Data-Driven Signal Processing Methods for Singing Voice Analysis
    (co-supervised with Prof. Meinard Müller)
  • Hans-Ulrich Berendes (2023): Differentiable Models for Piano Sound Synthesis
    (co-supervised with Prof. Meinard Müller)
  • Michael Fast (2022): Data-Driven Singing Reconstruction and Synthesis Techniques
    (co-supervised with Prof. Meinard Müller, Sebastian Rosenzweig, and Michael Krause)