Source Separation Tutorial Mini-Series III: Extensions and Interpretations to Non-Negative Matrix Factorization
Abstract: Building off the last two lectures in the series, we will continue our discussion on non-negative matrix factorization techniques for source separation. We will talk about common extensions, additional interpretations, methods of evaluation, and if time permits, future directions of research. Following the lecture, we will get a chance to program and improve our basic separator from the second lecture. Please bring your laptops with Matlab and/or Octave installed and be ready to code!
Slides + Code @ https://ccrma.stanford.edu/~njb/teaching/sstutorial/
Speaker Bios: Nicholas J. Bryan is a PhD candidate at the Center for Computer Research in Music and Acoustics (CCRMA) working with Prof. Ge Wang. His research interests are at the intersection between signal processing, machine learning, and human-computer interaction.
Dennis Sun is a PhD candidate in the Department of Statistics and working with Prof. Jonathan Taylor. His research interests are at the interface of statistics, signal processing, machine learning, and musicology.