This repository provides a code skeleton for the assignment1 of CompSci 235 in Semester 2, 2022.
Data sources:
The data files are modified excerpts downloaded from: https://www.loc.gov/item/2018655052 or https://github.com/mdeff/fma
We would like to acknowledge the authors of these papers for introducing the Free Music Archive (FMA), an open and easily accessible dataset of music collections:
Defferrard, M., Benzi, K., Vandergheynst, P., & Bresson, X. (2017). FMA: A Dataset for Music Analysis. In 18th International Society for Music Information Retrieval Conference (ISMIR).
Defferrard, M., Mohanty, S., Carroll, S., & Salathe, M. (2018). Learning to Recognize Musical Genre from Audio. In The 2018 Web Conference Companion. ACM Press.