8 citations · 8 across the 6 of their papers we have counts for
6 papers · 1 filter
Extending Music Annotation Schemas: Zero-Shot Prediction or Few-Shot Adaptation?
Christos Plachouras, Emmanouil Benetos, Johan Pauwels
Automatic music annotation is typically tackled under the assumption of a fixed annotation schema. In practice, commercial music catalogs often need to accommodate new musical attr…
Finetuning Strategies for Querying Sounds by Vocal Imitation
Aditya Bhattacharjee, Christos Plachouras, Sungkyun Chang +1
This technical report describes our winning submission to the AES AIMLA 2025 Challenge on querying sound effects by vocal imitation. We investigate two complementary fine-tuning st…
Learning Music Audio Representations With Limited Data
Christos Plachouras, Emmanouil Benetos, Johan Pauwels
Large deep-learning models for music, including those focused on learning general-purpose music audio representations, are often assumed to require substantial training data to ach…
Foundation Models for Music: A Survey
Yinghao Ma, Anders Øland, Anton Ragni +39
In recent years, foundation models (FMs) such as large language models (LLMs) and latent diffusion models (LDMs) have profoundly impacted diverse sectors, including music. This com…
mir_ref: A Representation Evaluation Framework for Music Information Retrieval Tasks
Christos Plachouras, Pablo Alonso-Jiménez, Dmitry Bogdanov
Music Information Retrieval (MIR) research is increasingly leveraging representation learning to obtain more compact, powerful music audio representations for various downstream MI…
Music Rearrangement Using Hierarchical Segmentation
Christos Plachouras, Marius Miron
Music rearrangement involves reshuffling, deleting, and repeating sections of a music piece with the goal of producing a standalone version that has a different duration. It is a c…