CIRE: A Chinese EEG Dataset for decoding speech intention modulated by prosodic emotion

CIRE, an EEG dataset, on spoken language interaction intention featuring aligned textual expressions with divergent intentional meanings due to the differences in prosodic emotion. The dataset comprises preprocessed high-density (128-channel) EEG recordings from 38 participants engaged in comprehension of attitude-conveying speech stimuli, accompanied by Wav2vec2-derived acoustic embeddings of the listening materials. The high-density and high temporal resolution EEG data offer broader application areas, both in cognitive neuroscience and speech BCI, and can also contribute to the brain-inspired algorithms.

CIRE是一款脑电图（Electroencephalogram，EEG）数据集，聚焦于口语交互意图研究。该数据集的核心特征为：即便与语音对齐的文本表达完全一致，不同的韵律情感仍会导致对应的交互意图含义产生分歧。该数据集包含38名参与者在理解带有态度传递的语音刺激时所采集的预处理后的高密度（128通道）脑电图记录，同时配套提供由Wav2vec2提取得到的受试语音材料声学嵌入特征。这款具备高密度特性与高时间分辨率的脑电图数据，在认知神经科学与语音脑机接口（Brain-Computer Interface，BCI）领域均拥有更广阔的应用场景，同时也可为类脑算法的研发提供重要支撑。

搜集汇总

背景与挑战

背景概述

CIRE是一个中文EEG数据集，旨在解码受韵律情感影响的语音意图。数据集包含38名参与者的高密度EEG记录和声学嵌入，适用于认知神经科学和语音脑机接口研究。