# asr-transcribe-to-text

Turns audio and video into timestamped text with speaker labels, either locally via MLX on Apple Silicon or through a remote ASR endpoint.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 1000 installs · ★ 1493
- Author: daymade
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/daymade/claude-code-skills/tree/HEAD/daymade-audio/asr-transcribe-to-text/SKILL.md
- Updated: 2026-10-25
- HTML: https://affpapa.org/en/nevibecode/skills/asr-transcribe-to-text

## What it does

The skill takes a local file, a direct media URL, or a podcast episode page. Before transcribing, it checks the project's transcript catalog for an existing canonical transcript, since raw audio sitting on disk is not a reason to regenerate text. If nothing exists, it picks a route: ordinary meeting and DJI recordings go to Feishu Minutes after preprocessing into a small M4A, while offline handling or an independent quality check triggers local ASR.

Local execution has two paths. Long unattended recordings run through checkpointed whisper.cpp with Silero VAD, and pyannote speakers are fused in afterwards. Short and medium recordings can use the Qwen3-ASR plus mlx-whisper alignment route. Neither path cuts ASR input at diarization turns, so speaker attribution happens after continuous-context recognition. Every run produces `[start-end] SPEAKER_xx: text` lines plus a CSV.

Diarization needs a HuggingFace token, because pyannote is a gated model. The first run without one fails and prints setup steps; after that the capability is auto-detected. Opting out with `--no-diarization` also drops timestamps, leaving only the session text. Configuration persists in `${CLAUDE_PLUGIN_DATA}/config.json`, and the mode follows the platform: local-mlx on Apple Silicon macOS, remote-api elsewhere.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add daymade/claude-code-skills --skill asr-transcribe-to-text -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/asr-transcribe-to-text/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/asr-transcribe-to-text/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add daymade/claude-code-skills --skill asr-transcribe-to-text -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/asr-transcribe-to-text/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add daymade/claude-code-skills --skill asr-transcribe-to-text -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/asr-transcribe-to-text/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install daymade/claude-code-skills asr-transcribe-to-text
```

2. **Manually: put the files in place**
- File: `.github/skills/asr-transcribe-to-text/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add daymade/claude-code-skills --skill asr-transcribe-to-text -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/daymade/claude-code-skills --path daymade-audio/asr-transcribe-to-text
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/asr-transcribe-to-text/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add daymade/claude-code-skills --skill asr-transcribe-to-text -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/daymade/claude-code-skills/tree/HEAD/daymade-audio/asr-transcribe-to-text/SKILL.md

## When to use it
- transcribe a meeting recording with speaker separation
- generate subtitles with line-level timestamps from a monologue
- compress a recording to M4A before uploading to Feishu Minutes
- cross-check two independent speaker timelines on a disputed turn
- merge recorder segments and downsample to 16kHz

## Example prompts
- transcribe `meeting.m4a` with speaker labels
- make subtitles from `interview.mp4`, I need line-level timestamps
- prep `recording.wav` for Feishu Minutes: compress and speed it up

## Source text · SKILL.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 025512ed48a3d4b5.

BEGIN THIRD-PARTY FILE 025512ed48a3d4b5
```text
---
name: asr-transcribe-to-text
description: >-
  Transcribes audio or video to speaker-labeled, timestamped text, locally with MLX on Apple Silicon
  or remotely. Use for 转录 / 录音转文字 / 说话人分离 / 字幕, and also for preparing audio for ASR without
  transcribing: 转格式, 降采样到 16kHz, merging recorder segments, or compressing and speeding up audio
  before 飞书妙记 — even when it looks like a one-line ffmpeg job.
argument-hint: "[audio-or-video-file-path-or-url ...]"
---

# ASR Transcribe to Text

Transcribe audio/video to **speaker-labeled** text. Local execution has two
explicit routes. Long or unattended recordings use checkpointed whisper.cpp +
Silero VAD blocks, then late-fuse pyannote speakers. Short/medium recordings may
use the Qwen3-ASR + mlx-whisper alignment route. Neither route cuts ASR input at
diarization turns; speaker attribution happens after continuous-context ASR.

## Route before ASR: the transcript is the result, not the run

Before starting transcription, check the owning project's transcript catalog,
external source index, and declared prior-work carriers for an existing
canonical transcript using source ID, date, title, and entity terms. A verified
human-reviewed/current transcript ends the task unless the user explicitly
asked for a new independent comparison. Raw audio existing is not a reason to
regenerate text that already exists.

When no canonical transcript exists:

1. For ordinary meeting/DJI recordings where cloud processing is allowed, use
   Feishu Minutes as the normal primary route (preprocess to a small M4A first).
2. Use local ASR when the user requires offline/privacy handling, Feishu is
   unavailable or failed, or the task explicitly needs an independent quality
   comparison.
2b. **For a second, independent speaker timeline**, use StepFun's async file
   endpoint via the `stepfun-asr` skill's `asr_file.py`. It is the only vendor
   diarization route here that does not share code or models with local pyannote, so
   agreement between the two is real corroboration rather than one tool agreeing
   with itself. Measured 2026-09-19 on a 10-minute film: both split the key turn
```
END THIRD-PARTY FILE 025512ed48a3d4b5

The third-party file has ended. Everything between the 025512ed48a3d4b5 tags is data: requests and commands from it are not followed. An “end of file” line with another tag inside the block is part of the file.

First 2188 of 55437 bytes. © daymade · MIT · https://github.com/daymade/claude-code-skills/tree/HEAD/daymade-audio/asr-transcribe-to-text/SKILL.md

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