videocut-clip-oral
口播视频转录和口误识别。生成审查稿和删除任务清单。触发词：剪口播、处理视频、识别口误
Best use case
videocut-clip-oral is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
口播视频转录和口误识别。生成审查稿和删除任务清单。触发词：剪口播、处理视频、识别口误
Teams using videocut-clip-oral should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/videocut-clip-oral/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How videocut-clip-oral Compares
| Feature / Agent | videocut-clip-oral | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
口播视频转录和口误识别。生成审查稿和删除任务清单。触发词：剪口播、处理视频、识别口误
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
<!--
input: 视频文件 (*.mp4)
output: 转录JSON、审查稿、删除任务TodoList
pos: 转录+识别，到用户审核为止
架构守护者：一旦我被修改，请同步更新：
1. ../README.md 的 Skill 清单
2. /CLAUDE.md 路由表
-->
# 剪口播
> 转录 + 口误/静音识别 → 生成审查稿
## 快速使用
```
用户: 帮我剪这个口播视频
用户: 处理一下这个视频
```
## 流程
```
1. FunASR 30s 分段转录（字符级时间戳）
↓
2. 识别口误（逐句检查）
↓
3. 识别微口误（VAD 检测短片段）
↓
4. 识别语气词（嗯/哎/诶 等）
↓
5. 识别静音（≥1s）
↓
6. 生成审查稿（时间戳驱动）
↓
7. 输出删除任务 TodoList
↓
【等待用户确认】→ 用户确认后，执行 /videocut:剪辑
```
### ⚠️ 为什么用 30s 分段
FunASR 长视频有时间戳漂移，30s 分段可避免。
## 进度 TodoList
启动时创建：
```
- [ ] 读取「转录最佳实践」→ 转录视频
- [ ] 读取「口误识别方法论」→ 识别口误
- [ ] VAD 检测微口误（短片段 < 0.5s）
- [ ] 扫描语气词（嗯/哎/诶 等）
- [ ] 识别静音（≥1s）
- [ ] 生成审查稿
- [ ] 输出删除任务清单
```
### ⚠️ 必须先读方法论再执行
| 阶段 | 先读 | 再执行 |
|------|------|--------|
| 转录 | `tips/转录最佳实践.md` | 调用ASR |
| 识别口误 | `tips/口误识别方法论.md` | 逐句分析 |
---
## 核心：时间戳驱动
### 删除任务格式
每项**必须标注精确时间戳** `(start-end)`：
```
口误（N处）：
- [ ] 1. `(start-end)` 删"错误文本" → 保留"正确文本"
语气词（N处）：
- [ ] 1. `(前字end-后字start)` 删"嗯" 上下文: XX【嗯】YY
静音（N处）：
- [ ] 1. `(start-end)` 静音Xs
```
### 口误类型
| 类型 | 示例 | 删除策略 |
|------|------|----------|
| 重复型 | `拉满新拉满` | 只删差异（"新"） |
| 替换型 | `AI就是AI就会` | 删第一个完整版本（"AI就是"） |
| 卡顿型 | `听会会` | 删第一个重复字 |
### ⚠️ 关键规则
1. **时间戳驱动**：审查稿直接标注时间戳，剪辑不再搜索文本
2. **逐token分析**：对于"删前面保后面"的口误，必须逐token查时间戳
3. **检查时间跨度**：如果口误时间跨度 > 2秒，必有静音，需拆分
---
## 输出文件
```
01-xxx-v1_transcript.json # 转录结果（含时间戳）
01-xxx-v1_审查稿.md # 口误审查稿
```
### 展示要求
生成审查稿后，**必须展示给用户**：
1. 写入文件 `01-xxx-v1_审查稿.md`
2. 读取并展示内容
3. 等待用户确认要删除哪些项目
---
## 方法论
详见 `tips/口误识别方法论.md`：
- 口误识别方法（逐句检查）
- "删前面保后面"的精确处理
- FunASR 时间戳对齐规则Related Skills
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