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Sound Design Entrainment

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geegl
sound-design-entrainment

Human physiological rhythms (heartbeat, breathing, brainwaves) synchronize with external sound rhythms. Sound designers can use this to guide audience states.

Overview

Publishergeegl
Repositorydirectorskills
Skill namesound-design-entrainment
Stars
68
Forks
7
Bundled files
1
LicenseMIT
Links
Skill sourceRepository
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by geegl on GitHub. Read the source before you install it.

Installation

Install the Sound Design Entrainment AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/geegl/directorskills/tree/main/output/books/sound-design/sound-design-entrainment
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/geegl/directorskills.git /tmp/directorskills
mkdir -p .claude/skills
cp -r /tmp/directorskills/output/books/sound-design/sound-design-entrainment .claude/skills/sound-design-entrainment
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Sound Design Entrainment in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Sound Design Entrainment on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Sound Design Entrainment is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

RIA++ Skill: 互引效应原则 (Entrainment Principle)

R — 原文 (Reading)

"互引是我们的身体和思想与外部节奏同步作用的一种特殊状态。心跳的节奏会跟音乐的节奏趋于一致。" — 声音设计 — David Sonnenschein, p.g_0021

I — 方法论骨架 (Interpretation)

互引效应（entrainment）是人体生理节律与外部声音节奏自动同步的现象：

  • 心跳会与音乐节奏趋同——慢节奏（60-70BPM）降低心率，快节奏（120+BPM）提升心率
  • 呼吸会与声音节奏趋同——录音工程删除笛声中的呼吸声会导致听众喘气
  • 脑波会与特定频率趋同——萨满鼓声引导进入Theta状态（白日梦/幻觉）

应用边界：

  • 64BPM（接近安静心跳）→促进放松和深度思考
  • 120BPM+→引起兴奋和急促呼吸
  • 爵士乐→非线性思维，适合解决冲突
  • 古典音乐→警觉和精神状态

A1 — 书中的应用 (Past Application)

案例 1: 萨满鼓声的脑波引导

  • 问题: 如何用声音引导听众进入特定意识状态？
  • 方法论的使用: 萨满仪式使用约4-4.5Hz的重复鼓声，这个频率接近Theta脑波（4-8Hz，对应白日梦/浅催眠状态）。持续的节奏性刺激使脑波自动与鼓声频率同步
  • 结论: 人体生理节律会自动与外部声音节奏同步——这就是互引效应的底层机制
  • 结果: 该原理被广泛应用于冥想音乐、ASMR和治疗性声音设计

案例 2: 动作片的BPM选择

  • 问题: 如何用配乐节奏让观众在动作场景中感到兴奋？
  • 方法论的使用: 动作片追逐场景的配乐通常选择120-140BPM，接近人在兴奋/紧张状态下的心跳频率。观众的心率会自动与音乐节奏趋同，从而在生理层面感到紧张和兴奋
  • 结论: BPM选择不是美学问题，而是生理操控问题

A2 — 触发场景 (Future Trigger) ★

用户会在什么情境下需要这个 skill?

  1. 用户需要让观众放松或紧张——通过BPM选择控制生理状态
  2. 用户在设计冥想/催眠/吸毒场景的声音——需要引导特定意识状态
  3. 用户觉得配乐节奏与画面不匹配——需要调整BPM与叙事节奏同步
  4. 用户在做游戏/VR的沉浸式音频——需要通过声音引导玩家状态

语言信号

  • "这里应该让观众放松/紧张"
  • "角色在吸毒/冥想/恐慌"
  • "节奏太快了/太慢了"
  • "怎么用声音控制情绪"
  • "BPM应该选多少"

与相邻 skill 的区分

  • 与 sound-design-contrast-drama 的区别: contrast-drama 处理音量/密度的对比，entrainment 处理节奏/频率对生理的同步效应。前者是"变化"，后者是"同步"
  • 与 sound-design-expectation 的区别: expectation 处理认知层面的预期，entrainment 处理生理层面的节律同步。前者影响"想法"，后者影响"心跳"

E — 可执行步骤 (Execution)

  1. 目标状态确定：明确你希望观众进入什么生理/情绪状态

  2. 节奏匹配：选择对应BPM的声音元素——放松用60-70BPM，紧张用120+BPM

  3. 渐进引导：不要突然改变节奏，用渐进变化引导观众生理节律

    • 🔴 判停条件: 若节奏匹配后测试观众的心率/呼吸未出现预期方向的变化，回到步骤1重新评估目标BPM是否在人体自然共振范围内；若渐进引导过程中观众报告不适感（头晕、心悸），回到步骤2降低BPM变化幅度或延长过渡时间

B — 边界 (Boundary) ★

反场景：纯对话场景（语言节奏主导）、新闻/功能性内容（不应操控情绪）。

失败模式：

  • 节奏与身体自然共振冲突——如重摇滚的切分导致肌肉失控
  • 节奏变化太突然——观众生理无法跟上
  • 文化差异——不同文化对节奏的生理反应可能不同

Common Failure Modes

反模式与常见错误

  • 不要用单一BPM贯穿整个场景——人体生理节律需要变化才能维持注意力，持续相同节奏会让观众进入"节律麻木"状态，互引效应逐渐失效。必须在场景内设计节奏变化点
  • 不要忽视文化差异对互引效应的影响——不同文化背景的听众对相同BPM的生理反应可能截然不同，西方听众觉得"放松"的60BPM在某些文化中可能引发不安
  • 不要在对话场景中强行施加互引效应——当语言节奏和音乐节奏冲突时，观众的生理节律会无所适从，导致焦虑感而非预期的情绪效果

作者的盲点 / 时代局限

David Sonnenschein 的声音设计理论源自传统电影声音制作，对数字时代的新声音形态（如 ASMR、空间音频、AI 生成音效）覆盖不足。他假设声音设计师有专业录音棚和拟音资源，独立创作者的低成本声音解决方案讨论较少。书中理论框架偏重感知心理学，对文化差异导致的声音审美差异（如东西方对沉默的不同理解）涉及有限。

此外，声音夹带效应的讨论基于西方音乐理论和感知心理学，对非西方音乐传统中的节奏夹带（如印度塔拉、非洲复合节奏）涉及有限。此外，他未充分讨论视觉节奏与听觉节奏的交互夹带效应。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Sound Design Entrainment AI skill do?

Human physiological rhythms (heartbeat, breathing, brainwaves) synchronize with external sound rhythms. Sound designers can use this to guide audience states.

Why use Sound Design Entrainment on TypingMind?

Because you install it once and use it with any model. Sound Design Entrainment is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Sound Design Entrainment in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/geegl/directorskills/tree/main/output/books/sound-design/sound-design-entrainment. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Sound Design Entrainment?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Sound Design Entrainment?

As many as you like. As long as a model supports skills, you can use Sound Design Entrainment with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Sound Design Entrainment AI skill free?

Yes. It is published on GitHub by geegl under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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