论语言相似性在非目标说话人验证试验中的影响
On the influence of language similarity in non-target speaker verification trials
AI总结：
本文研究跨语言非目标说话人验证中语言相似性的影响，发现训练语言内比较存在聚类效应，而未训练语言试验中分数与语言相似性相关。
摘要：
本文利用在VoxCeleb数据集的多语言和单语言变体上训练的最先进说话人验证系统ECAPA-TDNN，研究了跨语言非目标说话人验证试验中语言相似性的影响。我们对多语言Globalphone和LDC CTS上的分数分布模式分析表明，在涉及训练语言的说话人比较中存在聚类效应，即比较语言的选择对分数的影响极小。相反，在涉及未包含于说话人验证系统训练集中的语言的试验中，我们观察到语言相似性效应，分数与由语言分类系统测量的语言相似性相关，尤其是在使用多语言训练数据时。
英文摘要：
In this paper, we investigate the influence of language similarity in cross-lingual non-target speaker verification trials using a state-of-the-art speaker verification system, ECAPA-TDNN, trained on multilingual and monolingual variants of the VoxCeleb dataset. Our analysis of the score distribution patterns on multilingual Globalphone and LDC CTS reveals a clustering effect in speaker comparisons involving a training language, whereby the choice of comparison language only minimally impacts scores. Conversely, we observe a language similarity effect in trials involving languages not included in the training set of the speaker verification system, with scores correlating with language similarity measured by a language classification system, especially when using multilingual training data.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
