We present a multimodal dataset of 1020 hours of simultaneously recorded scalp electroencephalography (EEG), facial electromyography (EMG), and speech audio from three healthy native Japanese speakers during open-vocabulary overt speech. Recordings were acquired with three EEG systems-an ultra-high-density system (g.Pangolin) and two cap-type systems (g.SCARABEO and eegosports), spanning 62-128 channels-across many sessions over several months. Each session provides time-synchronized EEG, facial EMG, and audio, together with speech-event annotations and transcriptions. Although collected with speech decoding as a primary motivation, the dataset also supports work on multimodal signal processing, artifact modeling, longitudinal and cross-device adaptation, and EEG representation learning. Technical validation included power spectral density and event-related potential analyses across participants, devices, and tasks, which showed the expected 1/f spectral profile, task-related alpha-band attenuation, and time-locked evoked responses. The dataset is released in Brain Imaging Data Structure (BIDS) format via OpenNeuro under a CC0 waiver to support both speech-related and broader EEG research.

翻译：我们提出了一个包含1020小时多模态数据的数据集，同步记录了三位健康日语母语者在开放式词汇有声语音过程中的头皮脑电图（EEG）、面部肌电图（EMG）及语音音频。数据采集使用了三种EEG系统——超高密度系统（g.Pangolin）及两种帽式系统（g.SCARABEO和eegosports），覆盖62至128通道，并在数月内跨多次实验会话完成。每次会话均提供时间同步的EEG、面部EMG和音频，以及语音事件标注和转录文本。尽管该数据集的主要动机是语音解码，但它同样支持多模态信号处理、伪迹建模、纵向与跨设备自适应以及EEG表征学习的研究。技术验证包括跨被试、设备及任务的功率谱密度和事件相关电位分析，结果呈现了预期的1/f频谱特征、任务相关α频带衰减及时间锁定诱发响应。本数据集以脑成像数据结构（BIDS）格式通过OpenNeuro发布，采用CC0豁免协议，旨在支持语音相关及更广泛的EEG研究。