{"ID":2921753,"CreatedAt":"2026-06-02T02:42:49.606572591Z","UpdatedAt":"2026-06-03T05:56:00.181519634Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2606.01264","arxiv_id":"2606.01264","title":"A 1000-hour EEG-EMG-audio dataset of Japanese speech production","abstract":"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.","short_abstract":"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.Pa...","url_abs":"https://arxiv.org/abs/2606.01264","url_pdf":"https://arxiv.org/pdf/2606.01264v1","authors":"[\"Motoshige Sato\",\"Ilya Horiguchi\",\"Masakazu Inoue\",\"Kenichi Tomeoka\",\"Eri Hatakeyama\",\"Yuya Kita\",\"Atsushi Yamamoto\",\"Ippei Fujisawa\",\"Shuntaro Sasai\"]","published":"2026-05-31T14:30:46Z","proceeding":"q-bio.NC","tasks":"[\"q-bio.NC\",\"cs.HC\",\"cs.SD\",\"eess.AS\",\"eess.SP\"]","methods":"[]","has_code":false}