基于记忆的训练和测试范式,用于在表达性演讲中进行强大的语音身份识别,使用与事件相关的潜力分析
1Institute of Linguistics, Shanghai International Studies University.
Journal of visualized experiments : JoVE
|August 26, 2024
概括
听众可以区分熟悉的扬声器,即使在表达式的演讲. 这项研究使用脑电图 (EEG) 来显示大脑活动模式,特别是晚期积极成分 (LPC),区分已知的声音和未知的声音.
科学领域:
- 认知神经科学 认知神经科学
- 听觉感知是一种听觉感知.
- 语音处理 语音处理
背景情况:
- 语音识别对于沟通至关重要,但它如何与表达性语言一起运作还不完全理解.
- 目前研究语音识别的现有方法受到反应时间和准确度的限制.
- 电脑电图 (EEG) 可以实时测量语音识别过程中的认知过程.
研究的目的:
- 调查听众在表达性语言中如何识别熟悉的扬声器与不熟悉的扬声器.
- 开发和验证一种基于记忆的语音识别方法,使用EEG.
- 分析与区分已知的和未知的声音相关的大脑活动模式.
主要方法:
- 一个三步模式:语音名称关联 (培训),语音名称匹配 (检查) 和旧/新扬声器歧视 (测试).
- 测试涉及自信和怀疑的演讲形式.
- 使用64通道系统收集EEG数据,并使用RStudio和MATLAB中的ERP和统计方法分析大脑拓.
主要成果:
- 在熟悉的 (旧) 扬声器与不熟悉的 (新) 扬声器 (400-850 ms) 相比,在EEG中观察到一个扩大后期积极成分 (LPC).
- 旧/新效应在中部和后部电极中更为明显,对于可疑的形.
- 对于自信的前奏,旧/新效应在前部,中部和后部电极上是明显的.
结论:
- 这项研究证明了基于EEG的可靠方法,用于实时识别扬声器.
- 研究结果表明,在熟悉与不熟悉的声音之间,有不同的神经处理,受语音代词的影响.
- 实验设计可以作为研究扬声器特定暗示绑定和相关障碍的参考,如语音识别症.
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