A 1000-hour EEG-EMG-audio dataset of Japanese speech production
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | , , , , , , , , |
|---|---|
| Format: | Preprint |
| Publié: |
2026
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
| _version_ | 1866911738351321088 |
|---|---|
| author | Sato, Motoshige Horiguchi, Ilya Inoue, Masakazu Tomeoka, Kenichi Hatakeyama, Eri Kita, Yuya Yamamoto, Atsushi Fujisawa, Ippei Sasai, Shuntaro |
| author_facet | Sato, Motoshige Horiguchi, Ilya Inoue, Masakazu Tomeoka, Kenichi Hatakeyama, Eri Kita, Yuya Yamamoto, Atsushi Fujisawa, Ippei Sasai, Shuntaro |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2606_01264 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | A 1000-hour EEG-EMG-audio dataset of Japanese speech production Sato, Motoshige Horiguchi, Ilya Inoue, Masakazu Tomeoka, Kenichi Hatakeyama, Eri Kita, Yuya Yamamoto, Atsushi Fujisawa, Ippei Sasai, Shuntaro Neurons and Cognition Human-Computer Interaction Sound Audio and Speech Processing Signal Processing 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. |
| title | A 1000-hour EEG-EMG-audio dataset of Japanese speech production |
| topic | Neurons and Cognition Human-Computer Interaction Sound Audio and Speech Processing Signal Processing |
| url | https://arxiv.org/abs/2606.01264 |