arXiv cs.CL· Georgios Makridis, Stefanos Kampouris·· 11 小时前AI 评分20
Nedimo：一个基于证据的多语言 AI 助眠故事生成管线
Nedimo: An Evidence-Grounded Multilingual Pipeline for AI-Generated Sleep Stories
AI 导读
Nedimo 是一个多语言助眠故事生成与朗读管线，将确定性规划与 LLM 生成分离，用四阶段注意力递减塑造脚本，并校验结构与词汇约束。其 TTS 输出经段落感知拼接、两遍响度归一化和发布门控，按固定响度、响度范围和真峰值限值复测编码文件。系统不宣称临床疗效，仅定位为放松与注意力支持工具，产品数据将停止位置、重播、提前放弃和完成视为模糊行为代理。
正文 · 原文
Abstract:Generative audio systems can produce large libraries of personalized bedtime content, but ordinary media objectives (retention, completion, and novelty) are poorly aligned with the goal of supporting a transition toward sleep. Direct evidence for narrated bedtime audio in adults is mixed, and a recent active-controlled trial did not support such audio as a standalone treatment for sleep disturbance. We translate this uncertain evidence into conservative engineering requirements and present a multilingual pipeline for generating and narrating low-arousal sleep stories. The implemented prototype separates deterministic planning from large language model generation, represents content and delivery parameters explicitly, shapes each script through a four-phase attention taper, validates structural and lexical constraints, performs a bounded error-aware retry, and quarantines unresolved outputs. Provider-agnostic text-to-speech synthesis is followed by paragraph-aware joining, two-pass loudness normalization, and a publication gate that re-measures the saved, encoded file against fixed loudness, loudness-range, and true-peak limits. The product data model records stop position, replay, early abandonment, and completion while treating these events as ambiguous behavioral proxies rather than clinical outcomes. We contribute an evidence-to-requirement mapping, a traceable guardrail architecture with explicit acceptance thresholds, technical evaluation criteria, and a prospective protocol for testing sleep-onset effects. No clinical efficacy is claimed; the system is positioned as a relaxation and attentional-support tool whose benefit and possible reliance must be evaluated empirically.
| Comments: | 7 pages, 3 figures, 3 tables |
| Subjects: | Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Human-Computer Interaction (cs.HC); Sound (cs.SD) |
| Cite as: | arXiv:2610.40970 [cs.AI] |
| (or arXiv:2610.40970v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2610.40970 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Georgios Makridis [view email]
[v1]
Thu, 29 Oct 2026 20:58:10 UTC (17 KB)
来源：arXiv cs.CL · arxiv.org