Transcribe audio files into text or JSON using the Whisper model.
npx skills add https://github.com/trpc-group/trpc-agent-go --skill whisper
Please help me install this Agent Skill. Skill: whisper Source: https://github.com/trpc-group/trpc-agent-go/tree/main/benchmark/gaia/skills/whisper Command: npx skills add https://github.com/trpc-group/trpc-agent-go --skill whisper
Transcribing hours of audio manually is time-consuming and error-prone. This skill provides fast, accurate transcription of audio files into text using Whisper, enabling quick content indexing, search, and accessibility.
Run the transcription script with your audio file and an output path. Example: python3 scripts/transcribe.py input.mp3 output.txt --model base --format text
High-intent search queries and answers about installing and using this skill.
You can transcribe audio files to text and output JSON by running the transcription script with your input audio file, specifying an output path, and setting the output format to JSON. This requires Python 3.8+, the openai-whisper package, and FFmpeg.
Whisper transcription supports multiple languages with automatic language detection and provides optional timestamps. It transcribes audio recordings into plain text or JSON for downstream processing like content indexing and search.
Yes, you need FFmpeg installed alongside Python 3.8+ and the openai-whisper package to enable full audio transcription functionality. FFmpeg handles the underlying audio processing required by the Whisper model.
The best way to generate meeting transcripts is using the Whisper model to transcribe audio recordings into text. This provides fast, accurate transcription across multiple languages, creating searchable archives and captions from your audio files.
Yes, you can run audio transcription from the command line by executing the Python transcription script with your input audio file, an output path, and optional arguments for model size and output format like text or JSON.
The Whisper model requires Python 3.8+, the openai-whisper package, and FFmpeg for full functionality. Transcription accuracy depends on audio quality, and processing large audio files requires sufficient computational resources.
dislerExtracts audio, converts video to MP4 or WebM, and transcribes with Whisper via Python CLI.
buda-aiTranscribe audio and video into timestamped TXT, SRT, and JSON transcripts.
ChimeraFoundationaTranscribe and translate audio across 99 languages using Whisper.
SpillwaveSolutionsTranscribe audio and video to text using Whisper with markdown context grounding.
