While making an effort to address the gender bias in its neural machine translation (NMT) technologies, Google has recently released a newly adjusted dataset that comes to be able to improve the rate at which Google Translate accurately translates gendered language.
“This is a challenge because traditional NMT methods translate sentences individually, but gendered information is not always explicitly stated in each individual sentence.” – is stated by the AI team.
Based on the latest experiences and tests run against Wikipedia entries on a person, rock bands, teams it appears to improve significantly the gender guess and access, though there is still lot’s of job to be done. “It’s worth mentioning that by releasing this dataset, we don’t aim to be prescriptive in determining what’s the optimal approach to address gender bias,” the team shares. “This contribution aims to foster progress on this challenge across the global research community.”