Voxceleb2 Dataset

VoxCeleb2 is a large-scale dataset of human speech recordings used extensively to train and evaluate speaker recognition systems. Current research focuses on improving the robustness and efficiency of these systems, often employing techniques like knowledge distillation, self-supervised learning, and multimodal fusion (combining audio and visual data) with architectures such as ECAPA-TDNN and Wav2Vec 2.0. This work addresses challenges like limited data availability, noise robustness, and bias mitigation, ultimately aiming to enhance the accuracy and fairness of speaker verification technologies across diverse conditions and populations. The dataset's impact extends to various applications, including security, forensics, and personalized voice assistants.