local-transcript
SolidTranscribe a specified local video or audio file into cleaned final `.txt`, `.pdf`, or `.docx` transcripts using speech recognition with Apple Silicon GPU acceleration and optional LLM-based proofreading. Use when the user wants text extracted from a local media file path such as `.mp4`, `.mov`, `.mkv`, `.webm`, `.mp3`, `.m4a`, or `.wav`, and the output language should follow the spoken language in the media automatically. Prefer this skill for local-file transcription workflows that should produce cleaned transcripts with natural paragraphs, deterministic Chinese cleanup, and simplified Chinese output for Chinese speech. LLM proofreading is available but off by default.
Install
Quality Score: 85/100
Skill Content
Details
- Author
- johnqtcg
- Repository
- johnqtcg/awesome-skills
- Created
- 6 months ago
- Last Updated
- today
- Language
- Python
- License
- MIT
Integrates with
Similar Skills
Semantically similar based on skill content — not just same category
video-transcript
Use when the user provides a video URL or local media/caption file and wants the transcript/text稿, especially YouTube transcript extraction. Captions are used first; audio-only Whisper transcription is the fallback.
audio-transcribe
Transcribe local audio files (voice memos, meeting recordings, dictations, interviews; m4a/mp3/wav/opus/ogg/flac, also the audio track of local video files) in high quality via Whisper (configurable API endpoint) and place the transcript as a dated .md next to the source file. Use whenever the user drops an audio file, mentions a path to a recording, or wants its content as text: "transcribe this", "what do I say in the recording", "turn this into text", "summarize the memo", even without the word "transcribe". NOT for YouTube or podcast URLs; that is the video-watch skill.
clipsmith-audio-transcript
Convert a local audio file to text by running an explicit local transcription command. Use after extracting audio from video.