Face-voice Association in Multilingual Environments (FAME) Challenge 2024 Evaluation Plan

Muhammad Saad Saeed, Shah Nawaz, Muhammad Salman Tahir, Rohan Kumar Das, Muhammad Zaigham Zaheer +5 more
4/14/2024
cs.CVcs.SDeess.AS

No official code found. Best implementation: mavceleb/mavceleb_baseline (11 stars, last commit 2025-11-05).

Abstract

The advancements of technology have led to the use of multimodal systems in various real-world applications. Among them, the audio-visual systems are one of the widely used multimodal systems. In the recent years, associating face and voice of a person has gained attention due to presence of unique correlation between them. The Face-voice Association in Multilingual Environments (FAME) Challenge 2024 focuses on exploring face-voice association under a unique condition of multilingual scenario. This condition is inspired from the fact that half of the world's population is bilingual and most often people communicate under multilingual scenario. The challenge uses a dataset namely, Multilingual Audio-Visual (MAV-Celeb) for exploring face-voice association in multilingual environments. This report provides the details of the challenge, dataset, baselines and task details for the FAME Challenge.

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Code Implementations(1)

mavceleb/mavceleb_baselineCommunity100%
111PythonApr 4, 202411 months ago

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Cite this paper

@article{saeed2024facevoice,
  title  = {Face-voice Association in Multilingual Environments (FAME) Challenge 2024 Evaluation Plan},
  author = {Muhammad Saad Saeed and Shah Nawaz and Muhammad Salman Tahir and Rohan Kumar Das and Muhammad Zaigham Zaheer and Marta Moscati and Markus Schedl and Muhammad Haris Khan and Karthik Nandakumar and Muhammad Haroon Yousaf},
  year   = {2024},
  eprint = {2404.09342},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2404.09342v3}
}

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