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IIT Indore's HGAST Corrects Gender Errors in Speech Translation

IIT Indore's HGAST Corrects Gender Errors in Speech Translation
IIT Indore Develops AI Tool HGAST To Fix Gender Bias In Speech Translation From English To Hindi, Marathi And Gujarati · freepressjournal.in

Researchers at IIT Indore made an AI tool called HGAST.

It helps translation programs choose the right gendered words.

English often uses the same verb whether a man or woman is speaking.

Hindi, Marathi and Gujarati can use different verb forms for men and women.

Translation systems sometimes choose male forms when a woman is speaking.

HGAST listens to the voice and examines the sentence.

It then changes incorrect words while trying to preserve the original meaning and grammar.

The tool can be added to existing translation systems without retraining them.

Tests showed that translations became much more accurate for female speakers.

Key facts

Tool
HGAST, or Hierarchical Gender Arbitration for Speech Translation
Languages tested
English to Hindi, Marathi and Gujarati
Translation systems
Three existing systems, including Sarvam AI, were tested
Hindi result
Female-speaker accuracy rose from 83.15% to 98.88%
Gujarati result
Female-speaker accuracy rose from approximately 73–76% to nearly 96–97%
Marathi result
Female-speaker accuracy rose from approximately 90–93% to 100%; native Marathi reviewers independently validated 98.2%
Human evaluation
500 reviewers per language participated, with results broadly matching automated evaluations

Quotes

Dr Chandresh Kumar Maurya

IIT Indore researcher who led the HGAST development team

“HGAST demonstrates that gender-related translation errors can be addressed without retraining the underlying translation model. By combining speech and linguistic information with a controlled correction mechanism, the framework significantly reduces systematic misgendering while preserving translation accuracy,”
freepressjournal.in
“As more people across India rely on AI to translate speech, getting the basics right matters and correctly recognising who is speaking is about as basic as it gets. I'm glad to see our researchers tackling a problem that's easy to overlook but has a real impact on how fairly people are represented.”
rediff.com

Sources

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