Publications

Journal articles

Audio-based musical version identification: Elements and challenges.

F. Yesiler, G. Doras, R. M. Bittner, C. J. Tralie, and J. Serrà.
IEEE Signal Processing Magazine, Vol. 38, Issue 6, 2021 (to be published).
[Paper] [Supplementary website]

Peer-reviewed conference papers

Assessing algorithmic biases for musical version identification.

F. Yesiler, M. Miron, J. Serrà, and E. Gómez.
Proc. of the ACM International Conference on Web Search and Data Mining (WSDM), 2022.
[Paper]

Investigating the efficacy of music version retrieval systems for setlist identification.

F. Yesiler, E.Molina, J. Serrà, and E. Gómez.
Proc. of the IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), pp. 541-545, 2021.
[Paper] [Github]

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

F. Yesiler, J. Serrà, and E. Gómez.
Proc. of the 21th Int. Soc. for Music Information Retrieval Conf. (ISMIR), Montreal, Canada, 2020.
[Paper] [Github]

Combining musical features for cover detection.

G.Doras, F. Yesiler, J. Serrà, E. Gómez, and G. Peeters
Proc. of the 21th Int. Soc. for Music Information Retrieval Conf. (ISMIR), Montreal, Canada, 2020.
[Paper]

Accurate and scalable version identification using musically-motivated embeddings.

F. Yesiler, J. Serrà, and E. Gómez.
Proc. of the IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), pp. 21-25, Barcelona, Spain, 2020.
[Paper] [Github]

Da-TACOS: A dataset for cover song identification and understanding.

F. Yesiler, C. Tralie, A. Correya, D. F. Silva, P. Tovstogan, E. Gómez, and X. Serra.
Proc. of the 20th Int. Soc. for Music Information Retrieval Conf. (ISMIR), pp. 327-334, Delft, The Netherlands, 2019.
[Paper] [Github] [Website]

Makam recognition using extended pitch distribution features and multi-layer perceptrons.

F. Yesiler, B. Bozkurt, and X. Serra.
Proc. of the 15th Sound and Music Computing Conf. (SMC), pp. 249-53, Limassol, Cyprus, 2018.
[Paper] [Github]

A machine learning approach to classification of phonation modes in singing.

F. Yesiler, and R. Ramirez.
Proc. of the 15th Sound and Music Computing Conf. (SMC), Montreal, Canada, 2020.
[Paper] [Github]

Thesis

Analysis and automatic classification of phonation modes in singing.

F. Yesiler. Supervisor: R. Ramirez.
Universitat Pompeu Fabra, Barcelona, Spain, 2018.
[Dissertation] [Github]