Gender Bias Evaluation in Machine Translation for Amharic, Tigrinya, and Afaan Oromoo

Entitled “Gender Bias Evaluation in Machine Translation for Amharic, Tigrinya, and Afaan Oromoo”, this study highlights the presence of gender bias in machine translation systems for three low-resource African languages: Amharic, Tigrinya, and Afaan Oromoo. It shows that translation tools often assign stereotypical gender roles to professions, even when the source text is gender-neutral. Conducted … Read more

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IPAR is taking part in two working groups on the development of the national strategy on Artificial Intelligence 

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GRAIN has selected Kwara State University and its AI4WIA 2.0 project to jointly develop a GEDI matrix for use in the agricultural calendar.

As part of Phase II of the GRAIN (Gender and Responsible Artificial Intelligence Network) project, KWASU has been selected to take part in the co-development of a GEDI (Gender – Equality – Diversity – Inclusion) matrix. This selection forms part of an initiative to support existing AI solutions with a view to integrating the principles of equality into them in a structured manner … Read more

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A systematic review of the literature on the assessment and mitigation of bias in automatic speech recognition models for low-resource African languages

Entitled «A systematic review of the literature on the assessment and mitigation of bias in automatic speech recognition models for low-resource African languages», this study highlights a major challenge for inclusive artificial intelligence: biases related to gender, accent, dialect and linguistic under-representation, … Read more

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