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Furkan Yesiler

3 accepted papers

2024

STEMGEN: A Music Generation Model That Listens

ICASSP 2024accepted

End-to-end generation of musical audio using deep learning techniques has seen an explosion of activity recently. However, most models concentrate on generating fully mixed music in response to abstract conditioning information. In this work, we present an alternative paradigm for producing music ge…

Cited by 0SourceScholar
2021

Investigating the Efficacy of Music Version Retrieval Systems for Setlist Identification

ICASSP 2021accepted

The setlist identification (SLI) task addresses a music recognition use case where the goal is to retrieve the metadata and times-tamps for all the tracks played in live music events. Due to various musical and non-musical changes in live performances, developing automatic SLI systems is still a cha…

Cited by 0SourceScholar
2020

Accurate and Scalable Version Identification Using Musically-Motivated Embeddings

ICASSP 2020accepted

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 open problem, with much room for improvement, specially with regard to combining accuracy and scalability. In this paper, w…

Cited by 0SourceScholar