3 citations · 3 across the 8 of their papers we have counts for
8 papers
CoJEPA: Combining Contrastive Learning and JEPA for Global-Local Music Representations
Gabriel Meseguer-Brocal, Yuexuan Kong, Romain Hennequin
Joint-Embedding Predictive Architecture (JEPA) has shown strong performance in learning rich representations through self-supervised prediction in latent space. However, it typical…
What Makes a Good Layer? Assessing the Layer-Wise Intrinsic Properties of Music Foundation Models
Angelos-Nikolaos Kanatas, Yuexuan Kong, Pablo Alonso-Jiménez +2
Music foundation models are commonly used as frozen audio feature extractors, yet selecting which layer to extract from remains largely heuristic. Current practice defaults to fixe…
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…
Multi-Class-Token Transformer for Multitask Self-supervised Music Information Retrieval
Yuexuan Kong, Vincent Lostanlen, Romain Hennequin +2
Contrastive learning and equivariant learning are effective methods for self-supervised learning (SSL) for audio content analysis. Yet, their application to music information retri…
Emergent musical properties of a transformer under contrastive self-supervised learning
Yuexuan Kong, Gabriel Meseguer-Brocal, Vincent Lostanlen +2
In music information retrieval (MIR), contrastive self-supervised learning for general-purpose representation models is effective for global tasks such as automatic tagging. Howeve…
S-KEY: Self-supervised Learning of Major and Minor Keys from Audio
Yuexuan Kong, Gabriel Meseguer-Brocal, Vincent Lostanlen +2
STONE, the current method in self-supervised learning for tonality estimation in music signals, cannot distinguish relative keys, such as C major versus A minor. In this article, w…
STONE: Self-supervised Tonality Estimator
Yuexuan Kong, Vincent Lostanlen, Gabriel Meseguer-Brocal +3
Although deep neural networks can estimate the key of a musical piece, their supervision incurs a massive annotation effort. Against this shortcoming, we present STONE, the first s…
STraDa: A Singer Traits Dataset
Yuexuan Kong, Viet-Anh Tran, Romain Hennequin
There is a limited amount of large-scale public datasets that contain downloadable music audio files and rich lead singer metadata. To provide such a dataset to benefit research in…