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Sound Design Diegetic Taxonomy

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geegl
sound-design-diegetic-taxonomy

Sound-image relationship taxonomy: on-screen, off-screen, non-diegetic, acousmatic. Classifies any film sound by its relationship to the story world.

Overview

Publishergeegl
Repositorydirectorskills
Skill namesound-design-diegetic-taxonomy
Stars
68
Forks
7
Bundled files
1
LicenseMIT
Links
  • 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 Diegetic Taxonomy 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-diegetic-taxonomy
  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-diegetic-taxonomy .claude/skills/sound-design-diegetic-taxonomy
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Sound Design Diegetic Taxonomy 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 Diegetic Taxonomy 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 Diegetic Taxonomy 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: 声画关系分类体系 (Diegetic Taxonomy)

R — 原文 (Reading)

"画内声音(看得到声源)/画外声音(看不到声源但在故事中存在)/非剧情声音(故事人物听不到)。米歇尔·琼创造了'幻听'术语。" — 声音设计 — David Sonnenschein, p.g_0036

I — 方法论骨架 (Interpretation)

电影声音按与画面和故事世界的关系分为:

  1. 画内声音(On-screen):声源在画面中可见——嘴唇同步的对白、关门声、可见的脚步声。
  2. 画外声音(Off-screen):声源在故事空间中但画面外——环境声、画外喊叫、不可见的收音机。分为主动(引发好奇)和被动(营造氛围)。
  3. 非剧情声音(Non-diegetic):故事人物听不到——画外音旁白、戏剧配乐、夸张的音效。
  4. 幻听(Acousmatic):听到声音但看不到声源。"去幻听"(de-acousmatic):揭示声源的戏剧时刻(如《绿野仙踪》拉开帘子)。

这个分类决定了声音的叙事功能、情感距离和观众的心理参与方式。

A1 — 书中的应用 (Past Application)

案例 1:《教父》餐馆场景的画外火车声

  • 问题:阿尔·帕西诺首次杀人的紧张场景,如何用声音增强主观心理压力而不依赖画面信息?
  • 方法论的使用:火车声是画外声音——声源在故事空间中但画面外。它不属于角色的对话或动作,却逐渐增强,映射迈克尔内心的紧张升级。火车始终不出现,维持幻听状态直到枪响。
  • 结论:画外声音是构建主观紧张感的利器——声源不可见让观众持续"寻找",这种认知张力远超可见声源。

案例 2:《2001太空漫游》非剧情音乐与画内沉默的对位

  • 问题:太空场景中宇航员听不到任何声音(真空无声),但观众需要感受到壮美和恐惧,如何解决?
  • 方法论的使用:施特劳斯的《查拉图斯特拉如是说》是非剧情声音——故事人物听不到,但为观众提供宏大的情绪引导。画内声音极度克制(呼吸声、舱内设备声),与画外音乐形成分类对比。
  • 结论:画内/非剧情的分类切换是叙事节奏工具——从画内的"真实"突然切入非剧情的"宏大",能产生时间暂停般的震撼效果。

A2 — 触发场景 (Future Trigger) ★

场景1:设计一个场景中"听到但看不到"的声音。

  • 语言信号:"画外有什么声音?"

场景2:决定是否在画面上展示声源。

  • 语言信号:"要不要让观众看到是什么在响?"

场景3:设计一个"揭示"的戏剧时刻。

  • 语言信号:"什么时候揭开谜底?"

E — 可执行步骤 (Execution)

  1. 分类标注:对每个声音元素标注是画内/画外/非剧情/幻听

  2. 功能匹配:画外声音用于制造好奇和恐惧;非剧情声音用于引导情绪;幻听用于制造神秘

  3. 揭示设计:如有幻听元素,设计"去幻听"的时机——什么时候揭示声源?

    • 🔴 判停条件: 若分类标注后同一声音在不同场景中的画内/画外归属不一致导致叙事混乱,回到步骤1建立统一的声音分类参照表;若去幻听时机在测试中未能产生预期的悬念或冲击效果,回到步骤3重新评估揭示的前置铺垫是否充分

B — 边界 (Boundary) ★

反场景:纯纪录片(所有声音都是画内的"真实"声音)、广播剧(无画面参照)。

失败模式:

  • 画外声音过多导致观众困惑——不知道场景空间在哪里
  • 非剧情声音过于明显——打破叙事沉浸
  • 去幻听时机不对——太早失去悬念,太晚失去冲击力

反模式与常见错误

  • 不要混淆画外声音和非剧情声音——画外声音属于故事世界(角色能听到),非剧情声音不属于(角色听不到)。混淆两者会导致观众对场景空间的感知混乱,破坏叙事逻辑
  • 不要在幻听阶段停留太久——声音"只闻其声不见其人"的神秘感有时间限度,超过观众耐心后神秘感会变成烦躁感,去幻听的窗口期通常不超过场景总时长的2/3
  • 不要过度使用画外声音制造"廉价恐惧"——当观众发现每次画外声音都只是虚惊一场后,画外声音的悬念功能会被彻底透支

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,叙事声音分类体系(画内/画外/非叙境)的讨论基于经典电影理论,对现代混合叙事形式(如打破第四面墙、元叙事、互动影视)的声音分类挑战讨论不足。此外,他未充分讨论游戏和 VR 中叙境声音的特殊性。

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 Diegetic Taxonomy AI skill do?

Sound-image relationship taxonomy: on-screen, off-screen, non-diegetic, acousmatic. Classifies any film sound by its relationship to the story world.

Why use Sound Design Diegetic Taxonomy on TypingMind?

Because you install it once and use it with any model. Sound Design Diegetic Taxonomy 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 Diegetic Taxonomy 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-diegetic-taxonomy. 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 Diegetic Taxonomy?

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 Diegetic Taxonomy?

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

Is the Sound Design Diegetic Taxonomy 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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