Voxceleb-ESP: preliminary experiments detecting Spanish celebrities from their voices
Abstract
This paper presents VoxCeleb-ESP, a collection of pointers and timestamps to YouTube videos facilitating the creation of a novel speaker recognition dataset. VoxCeleb-ESP captures real-world scenarios, incorporating diverse speaking styles, noises, and channel distortions. It includes 160 Spanish celebrities spanning various categories, ensuring a representative distribution across age groups and geographic regions in Spain. We provide two speaker trial lists for speaker identification tasks, each of them with same-video or different-video target trials respectively, accompanied by a cross-lingual evaluation of ResNet pretrained models. Preliminary speaker identification results suggest that the complexity of the detection task in VoxCeleb-ESP is equivalent to that of the original and much larger VoxCeleb in English. VoxCeleb-ESP contributes to the expansion of speaker recognition benchmarks with a comprehensive and diverse dataset for the Spanish language.
Keywords
Cite
@article{arxiv.2401.09441,
title = {Voxceleb-ESP: preliminary experiments detecting Spanish celebrities from their voices},
author = {Beltrán Labrador and Manuel Otero-Gonzalez and Alicia Lozano-Diez and Daniel Ramos and Doroteo T. Toledano and Joaquin Gonzalez-Rodriguez},
journal= {arXiv preprint arXiv:2401.09441},
year = {2024}
}