Face-voice Association across LAnguages and Gender (FLAG) 2027 Challenge Evaluation Plan
Face--voice association models may rely on language or gender cues in the voice rather than on speaker-specific voice characteristics, which can lead to a performance deterioration when the model has to identify a multilingual speaker or distinguis same-gender speakers. To investigate these issues, we introduce the Face-voice Association across LAnguages and Gender (FLAG) 2027 Challenge. The challenge formulates face--voice association as a cross-modal verification task: given a voice, identify the speaker's face from a ``gallery'' of faces consisting of the speaker's face and a set of negative samples. Models are evaluated on identities not present in the training data (``unseen'') and b...
| Authors | Marta Moscati, Swapnil Khandoker, Muhammad Saad Saeed et al. |
|---|---|
| Primary category | cs.CV |
| Published | 15 September 2026 |
| Last updated at source | 15 September 2026 |
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