Title:
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Da-TACOS: A dataset for cover song identification and understanding
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Author:
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Yesiler, Furkan; Tralie, Chris; Correya, Albin Andrew; Silva, Diego F.; Tovstogan, Philip; Gómez Gutiérrez, Emilia, 1975-; Serra, Xavier
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Abstract:
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Comunicació presentada a: 20th annual conference of the International Society for Music Information Retrieval (ISMIR) celebrat del 4 al 8 de novembre de 2019 a Delft, Països Baixos. |
Abstract:
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This paper focuses on Cover Song Identification (CSI),
an important research challenge in content-based Music
Information Retrieval (MIR). Although the task itself is
interesting and challenging for both academia and industry scenarios, there are a number of limitations for the
advancement of current approaches. We specifically address two of them in the present study. First, the number of publicly available datasets for this task is limited,
and there is no publicly available benchmark set that is
widely used among researchers for comparative algorithm
evaluation. Second, most of the algorithms are not publicly shared and reproducible, limiting the comparison of
approaches. To overcome these limitations we propose
Da-TACOS, a DaTAset for COver Song Identification and
Understanding, and two frameworks for feature extraction
and benchmarking to facilitate reproducibility. Da-TACOS
contains 25K songs represented by unique editorial metadata plus 9 low- and mid-level features pre-computed with
open source libraries, and is divided into two subsets. The
Cover Analysis subset contains audio features (e.g. key,
tempo) that can serve to study how musical characteristics vary for cover songs. The Benchmark subset contains
the set of features that have been frequently used in CSI research, e.g. chroma, MFCC, beat onsets etc. Moreover, we
provide initial benchmarking results of a selected number
of state-of-the-art CSI algorithms using our dataset, and
for reproducibility, we share a GitHub repository containing the feature extraction and benchmarking frameworks. |
Abstract:
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This work is partially supported by the MIP-Frontiers
project, the European Union’s Horizon 2020 research and
innovation programme under the Marie Skłodowska-Curie
grant agreement No. 765068, and by TROMPA, the Horizon 2020 project 770376-2. |
Rights:
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© Furkan Yesiler, Chris Tralie, Albin Correya, Diego F.
Silva, Philip Tovstogan, Emilia Gómez, Xavier Serra. Licensed under a
Creative Commons Attribution 4.0 International License (CC BY 4.0).
Attribution: Furkan Yesiler, Chris Tralie, Albin Correya, Diego F.
Silva, Philip Tovstogan, Emilia Gómez, Xavier Serra. “Da-TACOS: A
Dataset for Cover Song Identification and Understanding”, 20th International
Society for Music Information Retrieval Conference, Delft, The
Netherlands, 2019.
https://creativecommons.org/licenses/by/4.0/
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Document type:
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Conference Object Article - Published version |
Published by:
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International Society for Music Information Retrieval (ISMIR)
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