STraDa: A Singer Traits Dataset

Fuente: arXiv
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Auteurs principaux: Kong, Yuexuan, Tran, Viet-Anh, Hennequin, Romain
Format: Preprint
Publié: 2024
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author Kong, Yuexuan
Tran, Viet-Anh
Hennequin, Romain
author_facet Kong, Yuexuan
Tran, Viet-Anh
Hennequin, Romain
contents There is a limited amount of large-scale public datasets that contain downloadable music audio files and rich lead singer metadata. To provide such a dataset to benefit research in singing voices, we created Singer Traits Dataset (STraDa) with two subsets: automatic-strada and annotated-strada. The automatic-strada contains twenty-five thousand tracks across numerous genres and languages of more than five thousand unique lead singers, which includes cross-validated lead singer metadata as well as other track metadata. The annotated-strada consists of two hundred tracks that are balanced in terms of 2 genders, 5 languages, and 4 age groups. To show its use for model training and bias analysis thanks to its metadata's richness and downloadable audio files, we benchmarked singer sex classification (SSC) and conducted bias analysis.
format Preprint
id arxiv_https___arxiv_org_abs_2406_04140
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle STraDa: A Singer Traits Dataset
Kong, Yuexuan
Tran, Viet-Anh
Hennequin, Romain
Sound
Audio and Speech Processing
There is a limited amount of large-scale public datasets that contain downloadable music audio files and rich lead singer metadata. To provide such a dataset to benefit research in singing voices, we created Singer Traits Dataset (STraDa) with two subsets: automatic-strada and annotated-strada. The automatic-strada contains twenty-five thousand tracks across numerous genres and languages of more than five thousand unique lead singers, which includes cross-validated lead singer metadata as well as other track metadata. The annotated-strada consists of two hundred tracks that are balanced in terms of 2 genders, 5 languages, and 4 age groups. To show its use for model training and bias analysis thanks to its metadata's richness and downloadable audio files, we benchmarked singer sex classification (SSC) and conducted bias analysis.
title STraDa: A Singer Traits Dataset
topic Sound
Audio and Speech Processing
url https://arxiv.org/abs/2406.04140