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

arXiv: https://arxiv.org/abs/2507.12356 · HTML: https://mlsanity.com/paper/2507.12356/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 28 references that are in the map.
- First posted on arXiv 16 Jul 2025.

## Builds on (most cited first, 1 of 1)

- [Robotic Speech Synthesis: Perspectives on Interactions, Scenarios, and Ethics](https://mlsanity.com/paper/2203.09599/) (2022)

## Built on by (most cited first, 1 of 1)

- [Disentangling Acoustic Cues in Alzheimer's Pathology and Perception: The Roles of Language and Gender](https://mlsanity.com/paper/2607.23977/) (2026)

## Abstract (arXiv)

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.