activity
20192021
collaborators

5 papers

cs.SD2021

Assessing Algorithmic Biases for Musical Version Identification

Furkan Yesiler, Marius Miron, Joan Serrà +1

Version identification (VI) systems now offer accurate and scalable solutions for detecting different renditions of a musical composition, allowing the use of these systems in indu…

cs.SD2021

Audio-based Musical Version Identification: Elements and Challenges

Furkan Yesiler, Guillaume Doras, Rachel M. Bittner +2

In this article, we aim to provide a review of the key ideas and approaches proposed in 20 years of scientific literature around musical version identification (VI) research and co…

cs.SD2021

Investigating the efficacy of music version retrieval systems for setlist identification

Furkan Yesiler, Emilio Molina, Joan Serrà +1

The setlist identification (SLI) task addresses a music recognition use case where the goal is to retrieve the metadata and timestamps for all the tracks played in live music event…

cs.SD2020

Less is more: Faster and better music version identification with embedding distillation

Furkan Yesiler, Joan Serrà, Emilia Gómez

Version identification systems aim to detect different renditions of the same underlying musical composition (loosely called cover songs). By learning to encode entire recordings i…

cs.SD2019

Accurate and Scalable Version Identification Using Musically-Motivated Embeddings

Furkan Yesiler, Joan Serrà, Emilia Gómez

The version identification (VI) task deals with the automatic detection of recordings that correspond to the same underlying musical piece. Despite many efforts, VI is still an ope…