activity
20182022
most citedPredicting emotion from music videos: exploring the relative contribution of visual and auditory information to affective responses

8 citations · 10 across the 3 of their papers we have counts for

collaborators

5 papers

cs.SD2022

Conditional Drums Generation using Compound Word Representations

Dimos Makris, Guo Zixun, Maximos Kaliakatsos-Papakostas +1

The field of automatic music composition has seen great progress in recent years, specifically with the invention of transformer-based architectures. When using any deep learning m…

cs.CV20228 cited

Predicting emotion from music videos: exploring the relative contribution of visual and auditory information to affective responses

Phoebe Chua, Dimos Makris, Dorien Herremans +2

Although media content is increasingly produced, distributed, and consumed in multiple combinations of modalities, how individual modalities contribute to the perceived emotion of…

cs.SD2021

Generating Lead Sheets with Affect: A Novel Conditional seq2seq Framework

Dimos Makris, Kat R. Agres, Dorien Herremans

The field of automatic music composition has seen great progress in the last few years, much of which can be attributed to advances in deep neural networks. There are numerous stud…

cs.SD20212 cited

Hierarchical Recurrent Neural Networks for Conditional Melody Generation with Long-term Structure

Zixun Guo, Makris Dimos, Herremans Dorien

The rise of deep learning technologies has quickly advanced many fields, including that of generative music systems. There exist a number of systems that allow for the generation o…

cs.SD2018

DeepDrum: An Adaptive Conditional Neural Network

Dimos Makris, Maximos Kaliakatsos-Papakostas, Katia Lida Kermanidis

Considering music as a sequence of events with multiple complex dependencies, the Long Short-Term Memory (LSTM) architecture has proven very efficient in learning and reproducing m…