mlsanityData to 7 Oct 2026

Neural Spelling: A Spell-Based BCI System for Language Neural Decoding

arXiv 2501.17489 ↗First posted 29 Jan 2025cs.HC cs.AIcited by 4

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Abstract (arXiv)

Brain-computer interfaces (BCIs) present a promising avenue by translating neural activity directly into text, eliminating the need for physical actions. However, existing non-invasive BCI systems have not successfully covered the entire alphabet, limiting their practicality. In this paper, we propose a novel non-invasive EEG-based BCI system with Curriculum-based Neural Spelling Framework, which recognizes all 26 alphabet letters by decoding neural signals associated with handwriting first, and then apply a Generative AI (GenAI) to enhance spell-based neural language decoding tasks. Our approach combines the ease of handwriting with the accessibility of EEG technology, utilizing advanced neural decoding algorithms and pre-trained large language models (LLMs) to translate EEG patterns into text with high accuracy. This system show how GenAI can improve the performance of typical spelling-based neural language decoding task, and addresses the limitations of previous methods, offering a scalable and user-friendly solution for individuals with communication impairments, thereby enhancing inclusive communication options.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 24 of its 82 references that are in the map. First posted on arXiv 29 Jan 2025.

Builds on

24 of 82 references.

References · 24

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12 more
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 3; 2026: 1.

4 papers.

  1. 2025Embracing Trustworthy Brain-Agent Collaboration as Paradigm Extension for Intelligent Assistive Technologiescited by 5
  2. 2025Foundation Models for Cross-Domain EEG Analysis Application: A Surveycited by 4
  3. 2025A Survey on Bridging EEG Signals and Generative AI: From Image and Text to Beyondcited by 3
  4. 2026BrainStack: Neuro-MoE with Functionally Guided Expert Routing for EEG-Based Language Decodingcited by 0