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FSD50K: An Open Dataset of Human-Labeled Sound Events
TLDR
FSD50K is introduced, an open dataset containing over 51 k audio clips totalling over 100 h of audio manually labeled using 200 classes drawn from the AudioSet Ontology, to provide an alternative benchmark dataset and thus foster SER research.
Freesound technical demo
TLDR
This demo wants to introduce Freesound to the multimedia community and show its potential as a research resource.
Freesound Datasets: A Platform for the Creation of Open Audio Datasets
Comunicacio presentada al 18th International Society for Music Information Retrieval Conference celebrada a Suzhou, Xina, del 23 al 27 d'cotubre de 2017.
General-purpose Tagging of Freesound Audio with AudioSet Labels: Task Description, Dataset, and Baseline
TLDR
The goal of the task is to build an audio tagging system that can recognize the category of an audio clip from a subset of 41 diverse categories drawn from the AudioSet Ontology.
Learning Sound Event Classifiers from Web Audio with Noisy Labels
TLDR
Experiments suggest that training with large amounts of noisy data can outperform training with smaller amounts of carefully-labeled data, and it is shown that noise-robust loss functions can be effective in improving performance in presence of corrupted labels.
Audio tagging with noisy labels and minimal supervision
TLDR
This paper presents the task setup, the FSDKaggle2019 dataset prepared for this scientific evaluation, and a baseline system consisting of a convolutional neural network.
Freesound 2: An Improved Platform for Sharing Audio Clips
Freesound.org is an online collaborative sound database where people from different disciplines share recorded sound clips under Creative Commons licenses. It was started in 2005 and it is being
Audio Commons: bringing Creative Commons audio content to the creative industries
TLDR
The Audio Commons Initiative is presented, which is aimed at promoting the use of open audio content and at developing technologies with which to support the ecosystem composed by content repositories, production tools and users.
Sound Sharing and Retrieval
TLDR
This chapter describes how to build an audio database by outlining different aspects to be taken into account and discusses metadata-based descriptions of audio content and different searching and browsing techniques that can be used to navigate the database.
Audio Clip Classification Using Social Tags and the Effect of Tag Expansion
Comunicacio presentada a la 53rd International Conference: Semantic audio, celebrada els dies 27 a 29 de gener de 2014 a Londres, Regne Unit.
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