Explore a 19-minute conference talk from the FAccT 2021 virtual event that delves into the cross-lingual generalization of translation gender bias. Examine the research conducted by W. Cho, J. Kim, J. Yang, and N. Kim, which investigates how gender bias manifests across different languages in machine translation systems. Gain insights into the challenges and implications of gender bias in multilingual contexts, and learn about potential strategies for mitigating these biases to improve the fairness and accuracy of translation technologies.
Towards Cross-Lingual Generalization of Translation Gender Bias
Association for Computing Machinery (ACM) via YouTube
Overview
Syllabus
Towards Cross-Lingual Generalization of Translation Gender Bias
Taught by
ACM FAccT Conference