用眼动轨迹控制生成文本的阅读难易度，让AI懂你的阅读节奏。
Controlling Reading Ease with Gaze-Guided Text Generation
- 通过预测眼动模式引导语言模型生成特定阅读行为的文本
- 实验显示可显著改变阅读时间和主观难度感知，效果明显
- 适合教育内容个性化和信息无障碍场景，尤其对语言学习者有用
阅读时的眼动方式能反映认知负荷。本文利用这一特性，开发了一种可控制文本阅读难易度的生成方法。该方法通过预测人类眼动模式，引导语言模型输出以诱发特定阅读行为。在母语与非母语英语使用者的眼动实验中，结果表明该方法能有效使生成文本变易读或难读，测量指标包括阅读时间与主观难度评分。统计分析显示，阅读行为变化主要源于影响词汇处理的特征。潜在应用包括信息无障碍化文本简化、个性化语言学习材料生成等。
原文摘要 · Abstract (English)
The way our eyes move while reading can tell us about the cognitive effort required to process the text. In the present study, we use this fact to generate texts with controllable reading ease. Our method employs a model that predicts human gaze patterns to steer language model outputs towards eliciting certain reading behaviors. We evaluate the approach in an eye-tracking experiment with native and non-native speakers of English. The results demonstrate that the method is effective at making the generated texts easier or harder to read, measured both in terms of reading times and perceived difficulty of the texts. A statistical analysis reveals that the changes in reading behavior are mostly due to features that affect lexical processing. Possible applications of our approach include text simplification for information accessibility and generation of personalized educational material for language learning.
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