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儿童的皮质语音跟踪在儿童-成年人和儿童-机器人互动中
Fatih Sivridag1, Nivedita Mani1
1Department for Psychology of Language, University of Gottingen.
Developmental psychology
|October 2, 2025
概括
孩子 孩子 孩子 孩子
科学领域:
- 认知神经科学 认知神经科学
- 人与计算机的交互
- 发展心理学 发展心理学
背景情况:
- 社会机器人中的合成语音缺乏自然性,影响了人机交互.
- 自然的语言特质对于有效的沟通至关重要,特别是与儿童的沟通.
- 像Furhat这样的社交机器人越来越多地用于交互式环境.
研究的目的:
- 为了比较儿童对社交机器人合成语音的神经反应与成年人的自然语音.
- 在人机器人和人成年人互动期间调查5岁儿童的皮质语音跟踪.
- 根据来源 (机器人与成年人) 来识别神经处理语音的差异.
主要方法:
- 脑电图 (EEG) 记录了5岁儿童的神经活动.
- 孩子们听了一个成年人和一个社交机器人 (Furhat) 讲述的故事.
- 皮质语音跟踪被测量以评估大脑对听觉刺激的反应.
主要成果:
- 孩子们展示了成人和机器人语言的皮质语音跟踪.
- 与儿童-成年人互动相比,儿童-机器人互动的峰值皮质语音跟踪发生在更大的时间延迟.
- 机器人合成语音的神经处理与儿童的自然语音不同.
结论:
- 儿童的大脑可以跟踪社交机器人的言语,但时间动态改变了.
- 优化机器人语音的时间延迟可能会增强儿童机器人互动.
- 这些发现对为儿童设计更具吸引力和有效的社交机器人有影响.
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