research data . Dataset . 2019

FSDnoisy18k

Eduardo Fonseca; Mercedes Collado; Manoj Plakal; Daniel P. W. Ellis; Frederic Font; Xavier Favory; Xavier Serra;
Open Access
  • Published: 03 Jan 2019
  • Publisher: Zenodo
Abstract
<p>FSDnoisy18k is an audio dataset collected with the aim of fostering the investigation of label noise in sound event classification. It contains 42.5 hours of audio across 20 sound classes, including a small amount of manually-labeled data and a larger quantity of real-world noisy data.</p> <p><strong>Data curators</strong></p> <p>Eduardo Fonseca and Mercedes Collado</p> <p><strong>Contact</strong></p> <p>You are welcome to contact Eduardo Fonseca should you have any questions at eduardo.fonseca@upf.edu.</p> <p><strong>Citation</strong></p> <p>If you use this dataset or part of it, please cite the following <strong><a href="https://arxiv.org/abs/1901.01189">IC...
Persistent Identifiers
Subjects
free text keywords: Sound event classification, audio dataset, label noise, loss function
Funded by
EC| AudioCommons
Project
AudioCommons
Audio Commons: An Ecosystem for Creative Reuse of Audio Content
  • Funder: European Commission (EC)
  • Project Code: 688382
  • Funding stream: H2020 | RIA
Validated by funder
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Dataset . 2019
Provider: Datacite
Zenodo
Dataset . 2019
Provider: Zenodo
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