论文标题
SASV挑战的Vicomtech欺骗感知生物识别系统
The Vicomtech Spoofing-Aware Biometric System for the SASV Challenge
论文作者
论文摘要
本文介绍了我们提出的针对欺骗意见的说话者验证挑战的集成系统。它由一个强大的欺骗感知验证系统组成，该系统使用说话者验证和从专门神经网络中提取的固定嵌入。首先，使用测试说法的扬声器验证和欺骗嵌入的集成网络用于计算基于欺骗的分数。然后将该分数与登录和测试话语中的说话者验证嵌入之间的余弦相似性进行线性结合，从而获得了最终的评分决策。此外，使用一级损失函数对集成网络进行训练，以区分目标试验和未经授权的访问。我们提出的系统在ASVSPOOF19数据库中进行了评估，与其他集成方法相比，表现出竞争性能。此外，我们测试了基于自我监督的学习的整合方法，最先进的说话者验证和反式系统，从而产生了高性能的语音生物识别系统。
This paper describes our proposed integration system for the spoofing-aware speaker verification challenge. It consists of a robust spoofing-aware verification system that use the speaker verification and antispoofing embeddings extracted from specialized neural networks. First, an integration network, fed with the test utterance's speaker verification and spoofing embeddings, is used to compute a spoof-based score. This score is then linearly combined with the cosine similarity between the speaker verification embeddings from the enrollment and test utterances, thus obtaining the final scoring decision. Moreover, the integration network is trained using a one-class loss function to discriminate between target trials and unauthorized accesses. Our proposed system is evaluated in the ASVspoof19 database, exhibiting competitive performance compared to other integration approaches. In addition, we test, along with our integration approach, state of the art speaker verification and antispoofing systems based on self-supervised learning, yielding high-performance speech biometric systems.
