Acoustic inspired brain-to-sentence decoder for logosyllabic language
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Le résumé fourni par la source
Abstract Many severe neurological diseases, such as stroke and amyotrophic lateral sclerosis, can impair or destroy the ability of verbal communication. Recent advances in brain-computer interfaces (BCIs) have shown promise in restoring communication by decoding neural signals related to speech or motor activities into text. Existing research on speech neuroprosthesis has predominantly focused on alphabetic languages, leaving a significant gap of logosyllabic languages such as Mandarin Chinese which are spoken by more than 15% of the world population. Logosyllabic languages pose unique challenges to brain-to-text decoding due to extended character sets (e.g., 50,000+ for Mandarin Chinese) and complex mapping between characters and pronunciation. To address these challenges, we established a speech BCI designed for Mandarin, decoding speech-related stereoelectroencephalography (sEEG) signals into coherent sentences. We leverage the unique acoustic features of Mandarin Chinese syllables, constructing prediction models for syllable components (initials, tones, and finals), and employ a language model to resolve pronunciation to character ambiguities according to the semantic context. This method leads to a high-performance decoder with a median character accuracy of 71.00% over the full character set, demonstrating huge potentials for clinical application. To our knowledge, we are the first to report brain-to-sentence decoding for logosyllabic languages over full character set with a large intracranial electroencephalography dataset.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Acoustic inspired brain-to-sentence decoder for logosyllabic language
- Date Crossref
- 05/11/2023
- Éditeur
- openRxiv
- Type
- posted-content
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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Second Affiliated Hospital of Zhejiang University pays non établi dans la noticeÉtablissement de santé
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Westlake University pays non établi dans la noticeUniversité ou école supérieure
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Beijing Normal University State Key Laboratory of Cognitive Neuroscience and Learning pays non établi dans la noticeUniversité ou école supérieure
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Tongji University Center for Speech and Language Processing pays non établi dans la noticeUniversité ou école supérieure
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University of Pennsylvania Department of Bioengineering pays non établi dans la noticeUniversité ou école supérieure
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New York University Department of Psychology pays non établi dans la noticeUniversité ou école supérieure
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Zhejiang University School of Medicine Second Affiliated Hospital Department of Neurosurgery pays non établi dans la noticeUniversité ou école supérieure
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School of Engineering Center of Excellence in Biomedical Research on Advanced Integrated-on-chips Neurotechnologies (CenBRAIN) pays non établi dans la noticeUniversité ou école supérieure
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School of Foreign Languages pays non établi dans la noticeUniversité ou école supérieure
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Clinical Research Center for Neurological Diseases of Zhejiang Province pays non établi dans la noticeStructure de recherche
Second Affiliated Hospital of Zhejiang University, Westlake University et State Key Laboratory of Cognitive Neuroscience and Learning — Beijing Normal University, avec 7 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.