Planned intervention: On Wednesday April 3rd 05:30 UTC Zenodo will be unavailable for up to 2-10 minutes to perform a storage cluster upgrade.
Published December 5, 2022 | Version v1
Dataset Restricted

MusAV Dataset

  • 1. Music Technology Group, Universitat Pompeu Fabra

Description

MusAV is a new public benchmark dataset for comparative validation of arousal and valence (AV) regression models for audio-based music emotion recognition. We built MusAV by gathering comparative annotations of arousal and valence on pairs of music tracks, using track audio previews and metadata from the Spotify API. The resulting dataset contains 2,092 track previews covering 1,404 genres, with pairwise relative AV judgments by 20 annotators and various subsets of the ground truth based on different levels of annotation agreement.

This repository contains the dataset metadata, audio track previews and metadata gathered from the Spotify API for the annotated chunks. Please see the companion website and the related GitHub repository for more information on how to use the dataset and evaluation scripts.

 

Citation

If you use the MusAV Dataset, please cite our ISMIR 2022 paper:

Bogdanov, D., Lizarraga-Seijas, X., Alonso-Jiménez, P., & Serra X. (2022). MusAV: A dataset of relative arousal-valence annotations for validation of audio models. International Society for Music Information Retrieval Conference (ISMIR 2022).

BibTeX: 

@conference {bogdanov2019mtg,
    author = "Bogdanov, Dmitry and Lizarraga-Seijas, Xavier and Alonso-Jiménez, Pablo and Serra, Xavier",
    title = "MusAV: A dataset of relative arousal-valence annotations for validation of audio models",
    booktitle = "International Society for Music Information Retrieval Conference (ISMIR 2022)",
    year = "2022",
    address = "Bengaluru, India",
    url = "http://hdl.handle.net/10230/54181"
}

 

Acknowledgments

This research was carried out under the project Musical AI - PID2019-111403GB-I00/AEI/10.13039/501100011033, funded by the Spanish Ministerio de Ciencia e Innovación and the Agencia Estatal de Investigación.

We thank all the annotators who participated in the creation of the dataset.

Files

Restricted

The record is publicly accessible, but files are restricted to users with access.

Request access

If you would like to request access to these files, please fill out the form below.

You need to satisfy these conditions in order for this request to be accepted:

Please include in the justification field your academic affiliation (if you have one) and a brief description of your research topics and why you would like to use this dataset. If you do not include this information we may not approve your request.

The audio track previews and metadata gathered from the Spotify API for the MusAV dataset are released for non-commercial scientific research purposes only. Any publication of results based on the data extracts of the Spotify database must cite Spotify as the source of the data.

The MusAV dataset is offered free of charge for internal non-commercial use only.  You may not redistribute, publically communicate or modify it, unless expressly permitted by the Universitat Pompeu Fabra (UPF) or by applicable law. The individual contents of the dataset may be protected by copyright, and a non-transferrable limited license to reproduce and use the same is granted for the indicated purpose only.
 
The dataset and its contents are made available on an “as is” basis and without warranties of any kind, including without limitation satisfactory quality and conformity, merchantability, fitness for a particular purpose, accuracy or completeness, or absence of errors. Subject to any liability that may not be excluded or limited by law, the UPF is not liable for, and expressly excludes, all liability for loss or damage however and whenever caused to anyone by any use of the MusAV dataset or any part of it.

PRIVACY POLICY:
Personal data of users provided through using the Download form is processed in accordance with the following policy: Responsibility. The personal data provided will be stored in file called "Projectes de recerca, desenvolupament i innovació", under the responsibility of Universitat Pompeu Fabra.

PURPOSES. The data is processed for the general purpose of carrying out research development and innovation studies, works or projects. In particular, but without limitation, the data is processed for the purpose of communicating with Licensee regarding any administrative and legal / judicial purposes.

COLLECTION. We collect personal data including name, surname, affiliation and email address. Only the data marked with a star is obligatory. Users must provide true and accurate personal profile data. Users must NOT upload any sensitive data regarding racial origin, trade union membership, religion, ideology and sexual life, the user's or third party's health, or relative to the commission of criminal offences or proceedings and associated penalties or fines.

DISCLOSURE. The data is kept confidential and not communicated to anyone.

CONFIDENTIALITY. Technical and organizational measures have been adopted to preserve and protect users' personal information from unauthorized use or access and from being altered, lost or misused, taking into account the technological state of art, the features of the information stored and the risks to which information is exposed.

USER RIGHTS. Rights to access, correct, cancel or object to data in these files may be exercised by applying in writing, including a photocopy of your identity card or equivalent to: Gerent. Universitat Pompeu Fabra. Pl. de la Mercè, 12. 08002 - Barcelona.

CONSENT. By sending a contact form, users expressly agree to this policy, including the sending of electronic communications.

You are currently not logged in. Do you have an account? Log in here

Additional details

Related works

Is described by
10230/54181 (Handle)