Route speech-to-text transcription to Parakeet or faster-whisper backends.
npx skills add https://github.com/ThePlasmak/super-transcribe --skill super-transcribe
Please help me install this Agent Skill. Skill: super-transcribe Source: https://github.com/ThePlasmak/super-transcribe/tree/main Command: npx skills add https://github.com/ThePlasmak/super-transcribe --skill super-transcribe
This Skill provides a single entry point for converting speech to text by automatically selecting the best backend (Parakeet or faster-whisper) and lazily loading dependencies on first use, simplifying setup and improving transcription performance.
Run a transcription with a single command to generate a transcript using the best available backend.
High-intent search queries and answers about installing and using this skill.
Auto-routing speech-to-text evaluates available backends like Parakeet and faster-whisper, selecting the optimal one for speed and accuracy. It simplifies setup by lazily loading dependencies on first use and adapting to hardware for efficient transcription.
Yes, you can generate srt and vtt subtitles with speaker diarization. The transcription supports multiple output formats including text, json, ass, lrc, ttml, csv, and html, while labeling speakers for meeting transcripts and podcasts.
Yes, faster-whisper supports multi-language translation and transcription. The system routes audio to this backend to detect languages and translate speech, adapting to input formats for efficient multi-language processing.
The best way to transcribe podcasts without manual setup is using a unified entry point that lazily loads required tools like faster-whisper and nemo_toolkit on first use. This automates environment configuration and routes audio to the best backend.
No, you do not strictly need a GPU to run pyannote.audio for speaker diarization. The system adapts to available hardware, configuring processing for either GPU or CPU to ensure transcription and diarization still function efficiently.
zcaceresDownload YouTube audio with yt-dlp and transcribe it to markdown using Whisper.
NanmiCoderParses SRT subtitle files into structured JSON with optional statistics and text output.
peteromalletTranscribe audio into text across 99 languages using Whisper models.
adiytharpansaTranscribes audio files to text or translated subtitles using the Whisper CLI locally without remote APIs.
