Voxceleb-ESP: preliminary experiments detecting Spanish celebrities from their voices
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Abstract (arXiv)
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.
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References · 6
- 2018VoxCeleb2: Deep Speaker Recognitioncited by 875
- 2017VoxCeleb: a large-scale speaker identification datasetcited by 732
- 2017Generalized End-to-End Loss for Speaker Verificationcited by 293
- 2020In defence of metric learning for speaker recognitioncited by 126
- 2019CN-CELEB: a challenging Chinese speaker recognition datasetcited by 48
- 2020The ins and outs of speaker recognition: lessons from VoxSRC 2020cited by 21
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