Music data analysis is a highly interdisciplinary research field with roots in music science, psychology, statistics, computer science, digital signal processing, and beyond. Application scenarios are often user-centered and include music recommendation and classification systems, artificial music generation, recognition of musical properties like tempo, structure, or instrumentation, music transcription, plagiarism detection, alignment of different modalities, etc. Various Artificial Intelligence methods like deep neural networks, automated machine learning, multi-objective optimisation try to solve related problems in an automatic and efficient way.
In this proseminar, current applications and research studies from state-of-the-art conferences (in particular, the International Society for Music Information Retrieval conference) will be presented.
Following tasks belong to the participation:
The seminar will take place at the Chair for Artificial Methodology (Theaterstr. 35-39, room 325), on Wednesdays during the summer term, 14:30-16:00.
The working language is English.
Registration to the seminar is handled via the SuPra system.
Prof. Dr. Holger H. Hoos
Chair Holder, Alexander von Humboldt Professor
E-mail: hh[at]aim[dot]rwth-aachen[dot]de
Phone: +49 241 80 21451
Dr. Igor Vatolkin
Assistant Professor (Akademischer Rat)
