arXiv cs.CL· Carlos Bruno, Luis Ricardo Santos·· 12 小时前AI 评分22
面向神经自适应通信界面：个性化语音与语言支持框架
Toward Neuroadaptive Communication Interfaces: A Framework for Personalized Speech and Language Support
AI 导读
该研究提出一个将语言呈现适配个体能力与交互过程的框架，把信息获取、用户需求估计与支持选择（含句子切分、象形图、可选语音输出）分离，行为反馈作为自适应主要依据，脑电图仅作为不确定性感知的补充信息源。研究设计分阶段评估，对比固定、行为自适应与神经自适应三类界面，核心问题是神经信息能否在强行为基线之上提升理解与沟通效率。
正文
Abstract:Speech and language technologies have expanded access to communication, but the support they provide is often fixed. The same linguistic or visual aid may help one user and hinder another, or become less useful as task demands change. This project proposes a framework for adapting language presentation to individual abilities and ongoing interaction. It separates access to a message from the estimation of user needs and from the selection of support, including sentence segmentation, pictograms, and optional spoken output. Behavioral feedback provides the primary evidence for adaptation; electroencephalography is considered an additional, uncertainty-aware source of information rather than a direct measure of comprehension. We specify a staged evaluation comparing fixed, behavior-adaptive, and neuroadaptive interfaces. The central question is whether neural information improves comprehension and communication efficiency beyond a strong behavioral baseline.
| Subjects: | Human-Computer Interaction (cs.HC); Computation and Language (cs.CL) |
| Cite as: | arXiv:2610.34457 [cs.HC] |
| (or arXiv:2610.34457v1 [cs.HC] for this version) | |
| https://doi.org/10.48550/arXiv.2610.34457 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Carlos Bruno [view email]
[v1]
Sun, 25 Oct 2026 17:23:42 UTC (345 KB)
来源：arXiv cs.CL · arxiv.org