1 citations · 2 across the 13 of their papers we have counts for
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Automatic Music Mixing using a Generative Model of Effect Embeddings
Eloi Moliner, Marco A. Martínez-Ramírez, Junghyun Koo +5
Music mixing involves combining individual tracks into a cohesive mixture, a task characterized by subjectivity where multiple valid solutions exist for the same input. Existing au…
Automatic Music Sample Identification with Multi-Track Contrastive Learning
Alain Riou, Joan Serrà, Yuki Mitsufuji
Sampling, the technique of reusing pieces of existing audio tracks to create new music content, is a very common practice in modern music production. In this paper, we tackle the c…
Towards Blind Data Cleaning: A Case Study in Music Source Separation
Azalea Gui, Woosung Choi, Junghyun Koo +5
The performance of deep learning models for music source separation heavily depends on training data quality. However, datasets are often corrupted by difficult-to-detect artifacts…
Attribution-by-design: Ensuring Inference-Time Provenance in Generative Music Systems
Fabio Morreale, Wiebke Hutiri, Joan Serrà +2
The rise of AI-generated music is diluting royalty pools and revealing structural flaws in existing remuneration frameworks, challenging the well-established artist compensation sy…
Leveraging Whisper Embeddings for Audio-based Lyrics Matching
Eleonora Mancini, Joan Serrà, Paolo Torroni +1
Audio-based lyrics matching can be an appealing alternative to other content-based retrieval approaches, but existing methods often suffer from limited reproducibility and inconsis…
Enhancing Neural Audio Fingerprint Robustness to Audio Degradation for Music Identification
R. Oguz Araz, Guillem Cortès-Sebastià, Emilio Molina +4
Audio fingerprinting (AFP) allows the identification of unknown audio content by extracting compact representations, termed audio fingerprints, that are designed to remain robust a…
Supervised contrastive learning from weakly-labeled audio segments for musical version matching
Joan Serrà, R. Oguz Araz, Dmitry Bogdanov +1
Detecting musical versions (different renditions of the same piece) is a challenging task with important applications. Because of the ground truth nature, existing approaches match…