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| Auteurs principaux: | , , , , , , , , , , |
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| Format: | Preprint |
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2024
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| Accès en ligne: | https://arxiv.org/abs/2405.06346 |
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| _version_ | 1866929339316043776 |
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| author | Hada, Rishav Husain, Safiya Gumma, Varun Diddee, Harshita Yadavalli, Aditya Seth, Agrima Kulkarni, Nidhi Gadiraju, Ujwal Vashistha, Aditya Seshadri, Vivek Bali, Kalika |
| author_facet | Hada, Rishav Husain, Safiya Gumma, Varun Diddee, Harshita Yadavalli, Aditya Seth, Agrima Kulkarni, Nidhi Gadiraju, Ujwal Vashistha, Aditya Seshadri, Vivek Bali, Kalika |
| contents | Existing research in measuring and mitigating gender bias predominantly centers on English, overlooking the intricate challenges posed by non-English languages and the Global South. This paper presents the first comprehensive study delving into the nuanced landscape of gender bias in Hindi, the third most spoken language globally. Our study employs diverse mining techniques, computational models, field studies and sheds light on the limitations of current methodologies. Given the challenges faced with mining gender biased statements in Hindi using existing methods, we conducted field studies to bootstrap the collection of such sentences. Through field studies involving rural and low-income community women, we uncover diverse perceptions of gender bias, underscoring the necessity for context-specific approaches. This paper advocates for a community-centric research design, amplifying voices often marginalized in previous studies. Our findings not only contribute to the understanding of gender bias in Hindi but also establish a foundation for further exploration of Indic languages. By exploring the intricacies of this understudied context, we call for thoughtful engagement with gender bias, promoting inclusivity and equity in linguistic and cultural contexts beyond the Global North. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_06346 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Akal Badi ya Bias: An Exploratory Study of Gender Bias in Hindi Language Technology Hada, Rishav Husain, Safiya Gumma, Varun Diddee, Harshita Yadavalli, Aditya Seth, Agrima Kulkarni, Nidhi Gadiraju, Ujwal Vashistha, Aditya Seshadri, Vivek Bali, Kalika Computation and Language Existing research in measuring and mitigating gender bias predominantly centers on English, overlooking the intricate challenges posed by non-English languages and the Global South. This paper presents the first comprehensive study delving into the nuanced landscape of gender bias in Hindi, the third most spoken language globally. Our study employs diverse mining techniques, computational models, field studies and sheds light on the limitations of current methodologies. Given the challenges faced with mining gender biased statements in Hindi using existing methods, we conducted field studies to bootstrap the collection of such sentences. Through field studies involving rural and low-income community women, we uncover diverse perceptions of gender bias, underscoring the necessity for context-specific approaches. This paper advocates for a community-centric research design, amplifying voices often marginalized in previous studies. Our findings not only contribute to the understanding of gender bias in Hindi but also establish a foundation for further exploration of Indic languages. By exploring the intricacies of this understudied context, we call for thoughtful engagement with gender bias, promoting inclusivity and equity in linguistic and cultural contexts beyond the Global North. |
| title | Akal Badi ya Bias: An Exploratory Study of Gender Bias in Hindi Language Technology |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2405.06346 |