在商业"语气"分析系统中,性别和种族偏见问题
Nicole R Holliday1, Paul E Reed2
1Department of Linguistics, University of California, Berkeley, Berkeley, California, United States of America.
PloS one
|February 28, 2025
概括
亚马逊Halo 亚马逊Halo 在线
科学领域:
- 语音技术 语言技术
- 人与计算机的交互
- 社会语言学 社会语言学
背景情况:
- 社会反语音技术 (SFST) 提供语音分析,但缺乏多样化的扬声器研究.
- 亚马逊Halo可穿戴设备提供语音反分数和定性描述符.
- 现有的研究还没有评估不同人口群体的SFST表现.
研究的目的:
- 为了评估亚马逊Halo的语音分析对不同种族和性别的美国英语说话者的表现.
- 为了识别Halo的"能量"和"积极性"分数以及定性音色描述符中的潜在偏差.
- 分析扬声器种族和性别对SFST语音评估的影响.
主要方法:
- 录制黑人和白人男人和女人阅读标准化的段落.
- 收集了亚马逊Halo的"能量"和"积极性"分数以及定性语音描述符.
- 分析了声学特性和扬声器人口统计数据,以评估分数变化.
主要成果:
- 亚马逊Halo的"能源"评级和定性描述器显示出对女性和黑人发言者的偏见.
- 哈洛的"积极性"评分与词汇情绪分析相关,显示说话者的变化最小.
- 根据说话者的种族和性别,观察到语音评价的显著差异.
结论:
- 像亚马逊Halo这样的SFST可能会延续和放大对边缘化群体的社会偏见.
- 语音分析技术中的算法偏差对来自不同背景的用户构成风险.
- 需要进一步的研究,以确保语音技术在所有演讲者之间提供公平的表现.
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