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20232026
most citedSynergy of Machine and Deep Learning Models for Multi-Painter Recognition

2 citations · 4 across the 10 of their papers we have counts for

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6 papers · 1 filter

cs.SD2026

Towards AI-Generated Music Plagiarism Detection as a Version Identification Problem

Fotis Koutsikos, Ioannis Prokopiou, Spyridon Kantarelis +6

The rapid expansion of text-to-music generative models challenges traditional paradigms of music creation and intellectual property. Plagiarism in this context is rarely an absolut…

cs.SD2025

Go witheFlow: Real-time Emotion Driven Audio Effects Modulation

Edmund Dervakos, Spyridon Kantarelis, Vassilis Lyberatos +2

Music performance is a distinctly human activity, intrinsically linked to the performer's ability to convey, evoke, or express emotion. Machines cannot perform music in the human s…

cs.SD2025

Exploring How Audio Effects Alter Emotion with Foundation Models

Stelios Katsis, Vassilis Lyberatos, Spyridon Kantarelis +2

Audio effects (FX) such as reverberation, distortion, modulation, and dynamic range processing play a pivotal role in shaping emotional responses during music listening. While prio…

cs.SD2024★ 1 cited

CHORDONOMICON: A Dataset of 666,000 Songs and their Chord Progressions

Spyridon Kantarelis, Konstantinos Thomas, Ioannis Liolitsas +3

Chord progressions encapsulate important information about music, pertaining to its structure and conveyed emotions. They serve as the backbone of musical composition, and in many…

cs.SD2024

MusicLIME: Explainable Multimodal Music Understanding

Theodoros Sotirou, Vassilis Lyberatos, Orfeas Menis Mastromichalakis +1

Multimodal models are critical for music understanding tasks, as they capture the complex interplay between audio and lyrics. However, as these models become more prevalent, the ne…

cs.SD2023★ 1 cited

Perceptual Musical Features for Interpretable Audio Tagging

Vassilis Lyberatos, Spyridon Kantarelis, Edmund Dervakos +1

In the age of music streaming platforms, the task of automatically tagging music audio has garnered significant attention, driving researchers to devise methods aimed at enhancing…