About this document
Assessing Gender Bias in Machine Translation: A Case Study With Google Translate by Xiaoyi Cheng is a document available to read on EtoBox.
The document discusses assessing gender bias in Google Translate by inputting gender-neutral sentences containing various job titles and analyzing the gender of pronouns in the translated output. It finds Google Translate exhibits a strong male bias, especially for STEM jobs, and fails to match real-world female participation rates.
- Author
- Xiaoyi Cheng
- Language
- EN