CIRE:一个中国的EEG数据集,用于解码语音意图,其调节方式是以情感为基础
Shengrui He1, Zhongjie Li2, Jianwu Dang1,3
1Tianjin Key Laboratory of Cognitive Computing and Application, College of Intelligence and Computing, Tianjin University, Tianjin, 300350, Tianjin, China.
Scientific data
|October 21, 2025
概括
本研究介绍了CIRE数据集,用于使用电脑电图 (EEG) 解码语音意图. 它可以研究相同文本背后的不同意图,推进脑机接口 (BCI) 技术.
科学领域:
- 认知神经科学 认知神经科学
- 神经技术的神经技术
- 语音处理 语音处理
背景情况:
- 解码语音意图对于大脑与计算机接口 (BCI) 的发展至关重要.
- 现有的数据集缺乏从相同文本解码语音意图的多样性.
- 普罗索迪克情感显著影响口语的解释.
研究的目的:
- 介绍CIRE数据集用于口语交互的意图.
- 促进关于解码细微语音意图的研究.
- 为了支持BCI和认知神经科学的进步.
主要方法:
- 从38名参与者收集了高密度 (128通道) 的EEG数据.
- 使用Wav2vec2衍生声学嵌入用于语音刺激.
- 应用信号处理,认知分析和机器学习用于验证.
主要成果:
- 通过基线模型实现了68.2%的跨主题分类准确度.
- 确定了意图差异的可解释的神经生理相关物.
- 证明了数据集在认知神经科学和BCI中的实用性.
结论:
- CIRE数据集解决了对多样化语音意图数据的需求.
- 高密度EEG数据支持认知神经科学和语音BCI应用.
- 这些发现有助于大脑启发的算法和BCI开发.
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