Face-voice association in multilingual environment challenge 2026 aims to investigate the face-voice association task in multilingual scenario. The challenge introduces English-German face-voice pairs to be utilized in the evaluation phase. To this end, we revisit the fusion and orthogonal projection for face-voice association by effectively focusing on the relevant semantic information within the two modalities. Our method performs favorably on the English-German data split and ranked 3rd in the FAME 2026 challenge by achieving the EER of 33.1.

翻译：多语言环境下的人脸-语音关联挑战赛（2026）旨在探究多语言场景中的人脸-语音关联任务。该挑战赛引入了英-德双语人脸-语音配对数据用于评估阶段。为此，我们通过有效聚焦于两种模态间的相关语义信息，重新审视了面向人脸-语音关联的融合与正交投影机制。我们的方法在英-德数据划分上表现优异，并以33.1%的等错误率在FAME 2026挑战赛中位列第三。