2 citations · 4 across the 10 of their papers we have counts for
13 papers
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…
An Empirical Study of Counterfactual Self-Explanations in LLMs
Giannis Kalyvas, Giorgos Filandrianos, Orfeas Menis Mastromichalakis +2
Large language models can easily generate explanations for their own outputs, but such self-explanations are not necessarily faithful to the model's behavior. We study this issue t…
Exploration of Perceptual Speech Features for Clinical Decision-Support in Mental Health Care
Vassilis Lyberatos, Edmund G. Dervakos, Eleni Adamidi +2
Speech and language technologies offer valuable opportunities for supporting mental health assessment through objective and interpretable cues. We present a systematic feature-base…
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…
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…
Music Interpretation and Emotion Perception: A Computational and Neurophysiological Investigation
Vassilis Lyberatos, Spyridon Kantarelis, Ioanna Zioga +3
This study investigates emotional expression and perception in music performance using computational and neurophysiological methods. The influence of different performance settings…
Semantic-Aware Interpretable Multimodal Music Auto-Tagging
Andreas Patakis, Vassilis Lyberatos, Spyridon Kantarelis +2
Music auto-tagging is essential for organizing and discovering music in extensive digital libraries. While foundation models achieve exceptional performance in this domain, their o…
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…
BERTtime Stories: Investigating the Role of Synthetic Story Data in Language Pre-training
Nikitas Theodoropoulos, Giorgos Filandrianos, Vassilis Lyberatos +2
We describe our contribution to the Strict and Strict-Small tracks of the 2nd iteration of the BabyLM Challenge. The shared task is centered around efficient pre-training given dat…
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…
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…
Employing Crowdsourcing for Enriching a Music Knowledge Base in Higher Education
Vassilis Lyberatos, Spyridon Kantarelis, Eirini Kaldeli +4
This paper describes the methodology followed and the lessons learned from employing crowdsourcing techniques as part of a homework assignment involving higher education students o…
Synergy of Machine and Deep Learning Models for Multi-Painter Recognition
Vassilis Lyberatos, Paraskevi-Antonia Theofilou, Jason Liartis +1
The growing availability of digitized art collections has created the need to manage, analyze and categorize large amounts of data related to abstract concepts, highlighting a dema…