Seminar on music knowledge extraction using machine learning
Seminar on music knowledge extraction using machine learning
Taking advantage of the researchers coming to Barcelona for the NIPS conference (https://nips.cc/), we are organizing this small and informal seminar at the UPF. The goal is to have an open discussion on various topics related to machine learning applied to music, but putting special emphasis on the knowledge extraction aspects of it. Registration open.
Taking advantage of the researchers coming to Barcelona for the NIPS conference (https://nips.cc/), we are organizing this small and informal seminar at the UPF. The goal is to have an open discussion on various topics related to machine learning applied to music, but putting special emphasis on the knowledge extraction aspects of it.
Program (abstracts below)
Organiser: Xavier Serra (Music Technology Group, DTIC-UPF)
15:00h - 16:30h Part 1
- Welcome - Xavier Serra (Music Technology Group, DTIC-UPF)
- Valentin Emiya (Aix-Marseille Université, CNRS): Optimal spectral transportation with application to music transcription
- Cédric Févotte (CNRS): Nonnegative matrix factorisation and some applications in audio signal processing
- Katherine M. Kinnaird (Brown University): Aligned Hierarchies - A Multi-Scale Structure-Based Representation for Music-Based Data Streams
16:30h - 17:15h - Coffee break and poster session
17:15h - 19:00h - Part 2
- Oriol Nieto (Pandora): Deep Learning for Large Scale Music Recommendation
- Sageev Oore (Saint Mary's University): TBC
- Colin Raffel (Google Brain): The Lakh MIDI Dataset: How it was Made, and How to Use it.
- Aäron Van den Oord (Google Deep Mind): WaveNet: A Generative Model for Raw Audio
All details and registration at the seminar's page