1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.SD2021
JS Fake Chorales: a Synthetic Dataset of Polyphonic Music with Human Annotation
Omar Peracha
High-quality datasets for learning-based modelling of polyphonic symbolic music remain less readily-accessible at scale than in other domains, such as language modelling or image c…
cs.SD2019★ 1 cited
GANkyoku: a Generative Adversarial Network for Shakuhachi Music
Omar Peracha, Shawn Head
A common approach to generating symbolic music using neural networks involves repeated sampling of an autoregressive model until the full output sequence is obtained. While such ap…
cs.SD2019
Improving Polyphonic Music Models with Feature-Rich Encoding
Omar Peracha
This paper explores sequential modelling of polyphonic music with deep neural networks. While recent breakthroughs have focussed on network architecture, we demonstrate that the re…