Voice Memo Transcribe

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name: voice-memo-transcribe description: > Transcribe Apple Voice Memos recordings to text, organize content, and save to Apple Notes. Workflow: iPhone Voice Memos → iCloud sync → Mac Voice Memos DB → transcribe → Apple Notes → iCloud sync back to iPhone. Requires macOS with iCloud-enabled Voice Memos. Uses faster-whisper for AI transcription with auto device detection. Triggers on: "语音备忘录", "录音转文字", "voice memo", "transcribe recording", "录音整理", "录音笔记". license: MIT-0

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Voice Memo Transcribe / 语音备忘录转写

Transcribe Apple Voice Memos on Mac and save organized notes to Apple Notes — syncing back to iPhone via iCloud.

将 iPhone 语音备忘录通过 iCloud 同步到 Mac 后，AI 转写为文字，整理内容，并存入 Mac 备忘录，再通过 iCloud 同步回 iPhone。

iPhone 录音 → iCloud 同步 → Mac 语音备忘录 → AI 转写 → 整理 → Mac 备忘录 → iCloud → iPhone 备忘录

Prerequisites / 前置条件

1. macOS with Voice Memos app / 运行语音备忘录的 Mac 2. iCloud sync enabled for both Voice Memos and Notes (System Settings → Apple ID → iCloud) / 已启用语音备忘录和备忘录的 iCloud 同步 3. Full Disk Access granted to terminal app (System Settings → Privacy & Security → Full Disk Access) / 终端已获取「完全磁盘访问权限」 4. ffmpeg — brew install ffmpeg 5. uv — brew install uv

Database & File Paths / 数据库与文件路径

Database / 数据库: ~/Library/Group Containers/group.com.apple.VoiceMemos.shared/Recordings/CloudRecordings.db

Audio files / 音频文件: ~/Library/Group Containers/group.com.apple.VoiceMemos.shared/Recordings/

Workflow / 工作流程

Step 1: List Voice Memos / 列出语音备忘录

python3 scripts/list_memos.py [options]

| Option | Description / 说明 | Default / 默认 | |--------|-------------|---------| | --limit N | Number of results / 返回数量 | 20 | | --offset N | Pagination offset / 分页偏移 | 0 | | --search TERM | Search by title / 按标题搜索 | — | | --after YYYY-MM-DD | Filter after date / 起始日期 | — | | --before YYYY-MM-DD | Filter before date / 截止日期 | — | | --json | JSON output / JSON 格式输出 | off |

Present results as numbered list: title, date, duration. Ask user which to transcribe.

以编号列表展示：标题、日期、时长。询问用户要转写哪些。

Error "Database not found" / 报错"数据库未找到" → Enable iCloud sync for Voice Memos, or grant Full Disk Access. / 启用语音备忘录的 iCloud 同步，或授予完全磁盘访问权限。

Step 2: Check Built-in Transcript / 检查内置转写

Some Voice Memos have Apple's embedded transcripts (tsrp atom):

部分语音备忘录包含 Apple 自动生成的转写文本（tsrp atom）：

python3 scripts/extract_transcript.py ".m4a"

If transcript found → skip to Step 4. If "no embedded transcript" → proceed to AI transcription.

如果找到转写文本 → 跳到第 4 步。如果显示 "no embedded transcript" → 进入 AI 转写。

Step 3: AI Transcription / AI 转写

uv run --with faster-whisper python3 scripts/transcribe.py "" [options]

| Option | Description / 说明 | Default / 默认 | |--------|-------------|---------| | --model | tiny/base/small/medium/large-v3 | base | | --language | zh, en, ja, etc. | auto-detect / 自动检测 | | --output PATH | Save transcript to file / 保存到文件 | stdout / 标准输出 | | --device | cpu/coreml/mps | auto-detect / 自动检测 |

Model guide (15 min audio, Apple Silicon M1) / 模型参考（15 分钟音频，Apple Silicon M1）： | Model | Time / 耗时 | RAM / 内存 | Quality / 质量 | |--------|------|-----|---------| | base | ~2 min | 1.5 GB | Good / 良好 | | small | ~5 min | 2 GB | Better / 较好 | | medium | ~10 min | 5 GB | Very good / 很好 |

Tip / 提示： Start with base for preview, re-run with small or medium for final output. / 先用 base 快速预览，再用 small 或 medium 获取最终结果。

Step 4: Organize Content / 整理内容

1. Read transcript, identify topics, speakers, key moments / 阅读转写文本，识别话题、发言者、关键时刻 2. Create structured summary with timestamps / 创建带时间戳的结构化摘要 3. Ask user for context corrections if unclear (relationships, names, topic labels) / 如有疑问，向用户确认（人物关系、姓名、话题标签） 4. Misidentified speakers/names make notes worse — always confirm / 错误的发言者识别会降低笔记质量——务必确认

Step 5: Save to Apple Notes / 保存到备忘录

# Write content to temp file / 将内容写入临时文件
python3 -c "
content = open('/dev/stdin').read()
with open('/tmp/note_content.txt', 'w') as f:
    f.write(content)
" <<< "$NOTE_BODY"
Create note in a specific folder / 在指定文件夹创建备忘录
osascript -e '
tell application "Notes"
    tell folder ""
        set noteTitle to "