Discogs-VINet-MIREX
Xavier Serra
R.O. Araz
J. Serrà
D. Bogdanov
MIREX 2024
2025
Abstract
This technical report presents our submission to the cover song identification task for the 2024 edition of the Music Information Retrieval Evaluation eXchange (MIREX). For this submission, we enhanced our Discogs-VINet model by changing the definition of an epoch, incorporating automatic mixed precision (AMP) during both training and inference, and sampling four versions per clique during triplet mining (which became possible with AMP). Due to this enhanced model’s performance on the Discogs-VI test set, we trained a new model from scratch using the entire Discogs-VI dataset, rather than just the training partition used in Discogs-VINet (a 45% increase in the number of versions). This enhanced and retrained model is named Discogs-VINet-MIREX.
Related Publications
We introduce Vid-CamEdit, a novel framework for video camera trajectory editing, enabling the re-synthesis of monocular videos along user-defined camera paths. This task is challenging due to its ill-posed nature and the limited multi-view video data for training. Traditiona…
Music editing is an important step in music production, which has broad applications, including game development and film production. Most existing zero-shot text-guided methods rely on pretrained diffusion models by involving forward-backward diffusion processes for editing…
We present Music Arena, an open platform for scalable human preference evaluation of text-to-music (TTM) models. Soliciting human preferences via listening studies is the gold standard for evaluation in TTM, but these studies are expensive to conduct and difficult to compare…
JOIN US
Shape the Future of AI with Sony AI
We want to hear from those of you who have a strong desire
to shape the future of AI.



