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Dataset for polyphonic sound event detection tasks in urban soundscapes: The synthetic polyphonic ambient sound source (SPASS) dataset

This paper presents the Synthetic Polyphonic Ambient Sound Source (SPASS) dataset, a publicly available synthetic polyphonic audio dataset. SPASS was designed to train deep neural networks effectively for polyphonic sound event detection (PSED) in urban soundscapes. SPASS contains synthetic recordin...

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Autores principales: Viveros-Muñoz, Rhoddy, Huijse, Pablo, Vargas, Victor, Espejo, Diego, Poblete, Victor, Arenas, Jorge P., Vernier, Matthieu, Vergara, Diego, Suárez, Enrique
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10514412/
https://www.ncbi.nlm.nih.gov/pubmed/37743885
http://dx.doi.org/10.1016/j.dib.2023.109552
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author Viveros-Muñoz, Rhoddy
Huijse, Pablo
Vargas, Victor
Espejo, Diego
Poblete, Victor
Arenas, Jorge P.
Vernier, Matthieu
Vergara, Diego
Suárez, Enrique
author_facet Viveros-Muñoz, Rhoddy
Huijse, Pablo
Vargas, Victor
Espejo, Diego
Poblete, Victor
Arenas, Jorge P.
Vernier, Matthieu
Vergara, Diego
Suárez, Enrique
author_sort Viveros-Muñoz, Rhoddy
collection PubMed
description This paper presents the Synthetic Polyphonic Ambient Sound Source (SPASS) dataset, a publicly available synthetic polyphonic audio dataset. SPASS was designed to train deep neural networks effectively for polyphonic sound event detection (PSED) in urban soundscapes. SPASS contains synthetic recordings from five virtual environments: park, square, street, market, and waterfront. The data collection process consisted of the curation of different monophonic sound sources following a hierarchical class taxonomy, the configuration of the virtual environments with the RAVEN software library, the generation of all stimuli, and the processing of this data to create synthetic recordings of polyphonic sound events with their associated metadata. The dataset contains 5000 audio clips per environment, i.e., 25,000 stimuli of 10 s each, virtually recorded at a sampling rate of 44.1 kHz. This effort is part of the project ``Integrated System for the Analysis of Environmental Sound Sources: FuSA System'' in the city of Valdivia, Chile, which aims to develop a system for detecting and classifying environmental sound sources through deep Artificial Neural Network (ANN) models.
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spelling pubmed-105144122023-09-23 Dataset for polyphonic sound event detection tasks in urban soundscapes: The synthetic polyphonic ambient sound source (SPASS) dataset Viveros-Muñoz, Rhoddy Huijse, Pablo Vargas, Victor Espejo, Diego Poblete, Victor Arenas, Jorge P. Vernier, Matthieu Vergara, Diego Suárez, Enrique Data Brief Data Article This paper presents the Synthetic Polyphonic Ambient Sound Source (SPASS) dataset, a publicly available synthetic polyphonic audio dataset. SPASS was designed to train deep neural networks effectively for polyphonic sound event detection (PSED) in urban soundscapes. SPASS contains synthetic recordings from five virtual environments: park, square, street, market, and waterfront. The data collection process consisted of the curation of different monophonic sound sources following a hierarchical class taxonomy, the configuration of the virtual environments with the RAVEN software library, the generation of all stimuli, and the processing of this data to create synthetic recordings of polyphonic sound events with their associated metadata. The dataset contains 5000 audio clips per environment, i.e., 25,000 stimuli of 10 s each, virtually recorded at a sampling rate of 44.1 kHz. This effort is part of the project ``Integrated System for the Analysis of Environmental Sound Sources: FuSA System'' in the city of Valdivia, Chile, which aims to develop a system for detecting and classifying environmental sound sources through deep Artificial Neural Network (ANN) models. Elsevier 2023-09-07 /pmc/articles/PMC10514412/ /pubmed/37743885 http://dx.doi.org/10.1016/j.dib.2023.109552 Text en © 2023 The Authors. Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Viveros-Muñoz, Rhoddy
Huijse, Pablo
Vargas, Victor
Espejo, Diego
Poblete, Victor
Arenas, Jorge P.
Vernier, Matthieu
Vergara, Diego
Suárez, Enrique
Dataset for polyphonic sound event detection tasks in urban soundscapes: The synthetic polyphonic ambient sound source (SPASS) dataset
title Dataset for polyphonic sound event detection tasks in urban soundscapes: The synthetic polyphonic ambient sound source (SPASS) dataset
title_full Dataset for polyphonic sound event detection tasks in urban soundscapes: The synthetic polyphonic ambient sound source (SPASS) dataset
title_fullStr Dataset for polyphonic sound event detection tasks in urban soundscapes: The synthetic polyphonic ambient sound source (SPASS) dataset
title_full_unstemmed Dataset for polyphonic sound event detection tasks in urban soundscapes: The synthetic polyphonic ambient sound source (SPASS) dataset
title_short Dataset for polyphonic sound event detection tasks in urban soundscapes: The synthetic polyphonic ambient sound source (SPASS) dataset
title_sort dataset for polyphonic sound event detection tasks in urban soundscapes: the synthetic polyphonic ambient sound source (spass) dataset
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10514412/
https://www.ncbi.nlm.nih.gov/pubmed/37743885
http://dx.doi.org/10.1016/j.dib.2023.109552
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