16 papers
Improved Robustness in AI-Generated Music Detection
Emile Dugelay, Thomas Barand, Baptiste Campeas +3
The paper introduces a detection pipeline for AI-generated music that remains robust to simple audio manipulations such as speed or pitch changes by mapping audio to a log-frequenc…
Detection of AI-generated stems within hybrid human-AI music
François Rigaud, Gabriel Meseguer-Brocal, Benjamin Martin +1
The paper investigates how to detect AI‑generated stems in hybrid human‑AI music tracks, proposing a parallel architecture that combines source‑separation‑based energy estimation w…
Finding the noise: Zero-shot AI Music Detection
Darius Afchar, Romain Hennequin
We present a novel method for AI-generated music detection in scenarios where the models that generated the input samples are unknown to the detector (e.g., from a newly released s…
GraphLit: Learning Text-Enriched Dynamic Character Network Representations for Literary Study
Gaspard Michel, Elena V. Epure, Romain Hennequin +2
Methods to represent literary texts as graphs or sequences of graphs mainly focus on representing character interactions, and often overlook another crucial aspect: the textual con…
Beyond Musical Descriptors: Extracting Preference-Bearing Intent in Music Queries
Marion Baranes, Romain Hennequin, Elena V. Epure
Although annotated music descriptor datasets for user queries are increasingly common, few consider the user's intent behind these descriptors, which is essential for effectively m…
Perceived Femininity in Singing Voice: Analysis and Prediction
Yuexuan Kong, Viet-Anh Tran, Romain Hennequin
This paper focuses on the often-overlooked aspect of perceived voice femininity in singing voices. While existing research has examined perceived voice femininity in speech, the sa…