A CSMT challenge dataset for the identification of computer generated melodies
Year: 2020
Type: preprint
Abstract: In this paper, the dataset used for the data challenge organised by Conference on Sound and Music Technology (CSMT) is introduced. The CSMT data challenge requires participants to identify whether a given piece of melody is generated by computer or is composed by human. The dataset is formed by two parts: development dataset and evaluation dataset. The development dataset contains only computer generated melodies whereas the evaluation dataset contain both computer generated melodies and human composed melodies. The aim of the dataset is to examine whether it is possible to distinguish computer generated melodies by learning the feature of generated melodies.
Source: arXiv (Cornell University)
Authors: Shengchen Li, Yinji Jing, Georgy Fazekas
Language: English
Topic: Music and Audio Processing
Subfield: Signal Processing
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3112683371