Exploring Gender Bias in Alzheimer's Disease Detection: Insights from Mandarin and Greek Speech Perception
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arXiv
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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866912486169509888 |
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| author | He, Liu Li, Yuanchao Feng, Rui Han, XinRan Liu, Yin-Long Yang, Yuwei Zhu, Zude Yuan, Jiahong |
| author_facet | He, Liu Li, Yuanchao Feng, Rui Han, XinRan Liu, Yin-Long Yang, Yuwei Zhu, Zude Yuan, Jiahong |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_12356 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Exploring Gender Bias in Alzheimer's Disease Detection: Insights from Mandarin and Greek Speech Perception He, Liu Li, Yuanchao Feng, Rui Han, XinRan Liu, Yin-Long Yang, Yuwei Zhu, Zude Yuan, Jiahong Computation and Language Human-Computer Interaction Sound 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. |
| title | Exploring Gender Bias in Alzheimer's Disease Detection: Insights from Mandarin and Greek Speech Perception |
| topic | Computation and Language Human-Computer Interaction Sound |
| url | https://arxiv.org/abs/2507.12356 |