arXiv cs.CL· Yiqian Yang, Yiqun Duan, Chenyu Liu, Yiqi Wang, Xinliang Zhou, Chin-Teng Lin, Yu Zhang·· 2 天前AI 评分27
脑到语言解码综述：任务、信号、方法、评估与实际应用
Brain-to-Language Decoding: Tasks, Signals, Methods, Evaluation, Practical Use and Beyond
AI 导读
一篇综述系统梳理了脑到语言解码研究，将神经活动转化为语言或表达输出，涵盖侵入式与非侵入式测量，检索无年份下限、来源更新至 2026 年 9 月。文章把 Articulated、Inner、Perceived 三类任务与其涉及的神经元群体、解码器可用表征及输出对应起来，并比较已发表性能与通信成本。
正文 · 原文
Abstract:Brain-to-language decoding translates neural activity associated with language production, internal speech and perception into linguistic or expressive outputs. It offers a route to restoring communication after speech loss and a means of studying how the brain represents language. Advances in neural recording and representation learning have expanded the field from constrained recognition and acoustic reconstruction to text generation, streaming personalised speech and facial animation. This survey synthesises these developments across invasive and non-invasive measurements, drawing on a search without a lower year limit and source-led updates through September 2026. We connect Articulated, Inner and Perceived tasks to the neural populations they engage, the representations available to decoders and the outputs those representations can support. We examine model development, public resources and the evolution of evaluation, and compare published performance and communication costs within their reported protocols. The synthesis identifies complementary routes to progress: phonetic, acoustic and semantic targets preserve different aspects of a message; shared representations support reuse across recording conditions and tasks; and online communication increasingly depends on calibration, feedback and user control alongside decoding accuracy. Shared benchmarks enable algorithmic comparisons, while longitudinal studies reveal the demands of sustained use. We discuss these developments and their remaining limitations, then outline a prospective five-level trajectory from commands and language to meaning, scenarios and bidirectional cognitive exchange
| Subjects: | Computation and Language (cs.CL); Human-Computer Interaction (cs.HC); Neural and Evolutionary Computing (cs.NE) |
| Cite as: | arXiv:2609.27650 [cs.CL] |
| (or arXiv:2609.27650v3 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2609.27650 arXiv-issued DOI via DataCite |
Submission history
From: Yiqian Yang [view email]
[v1]
Wed, 23 Sep 2026 10:14:47 UTC (21,336 KB)
[v2]
Thu, 24 Sep 2026 02:08:45 UTC (21,443 KB)
[v3]
Thu, 15 Oct 2026 03:34:46 UTC (21,987 KB)
来源：arXiv cs.CL · arxiv.org