Exploring Gender Bias in Alzheimer's Disease Detection: Insights from Mandarin and Greek Speech Perception Article Swipe

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He Liu , Yuanchao Li , Rui Feng , X Han , Yin-Long Liu , Yuwei Yang , Zude Zhu , Jiahong Yuan ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.48550/arxiv.2507.12356

Gender bias has been widely observed in speech perception tasks, influenced by the fundamental voicing differences between genders. This study reveals a gender bias in the perception of Alzheimer's Disease (AD) speech. In a perception experiment involving 16 Chinese listeners evaluating both Chinese and Greek speech, we identified that male speech was more frequently identified as AD, with this bias being particularly pronounced in Chinese speech. Acoustic analysis showed that shimmer values in male speech were significantly associated with AD perception, while speech portion exhibited a significant negative correlation with AD identification. Although language did not have a significant impact on AD perception, our findings underscore the critical role of gender bias in AD speech perception. This work highlights the necessity of addressing gender bias when developing AD detection models and calls for further research to validate model performance across different linguistic contexts.

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Type: preprint
Language: en
Landing Page: http://arxiv.org/abs/2507.12356
PDF: https://arxiv.org/pdf/2507.12356
OA Status: green
OpenAlex ID: https://openalex.org/W4415142812

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DOI: https://doi.org/10.48550/arxiv.2507.12356

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Title: Exploring Gender Bias in Alzheimer's Disease Detection: Insights from Mandarin and Greek Speech Perception

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Type: preprint

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Language: en

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Publication year: 2025

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Publication date: 2025-07-16

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Authors: He Liu, Yuanchao Li, Rui Feng, X Han, Yin-Long Liu, Yuwei Yang, Zude Zhu, Jiahong Yuan

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Landing page: https://arxiv.org/abs/2507.12356

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PDF URL: https://arxiv.org/pdf/2507.12356

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OA URL: https://arxiv.org/pdf/2507.12356

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Cited by: 0

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