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.

VoxCeleb-ESP 是一个新的说话人识别数据集，包含 160 位西班牙名人，涵盖了各个年龄组和地理区域，提供了两个说话人辨识任务的试验列表，并伴有基于跨语言评估的 ResNet 预训练模型，初步结果表明 VoxCeleb-ESP 在说话人识别方面的复杂性与原始且更大规模的英语数据集 VoxCeleb 相当。VoxCeleb-ESP 为西班牙语提供了一个全面且多样化的说话人识别基准数据集。