Asr Transcribe To Text
Transcribes audio or video to speaker-labeled, timestamped text, locally with MLX on...
Install
npx skills add daymade/claude-code-skills --skill asr-transcribe-to-text -g -a claude-code -y- Repository
- daymade/claude-code-skills1.5k
- Category
- Media
- Updated
- 3d ago
- License
- MIT
- Context cost
- Mediumabout 3,000 tokens
- Runs scripts
- Yes, review before use
What it does
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.
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
Preserve course videos before choosing an ASR route. When uploading a course video, or when the user requires the picture or original media, upload the original video file with its picture, audio and original speed. Skip Step 2 and the preprocessing section unless the user explicitly requests conversion. An existing transcript can satisfy the text request but does not satisfy an outstanding video upload. Slow transfers or upload failures do not authorize extracting audio, transcoding or speeding up the video.
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 transcription 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:
