whisper
Category: multimodal-and-emerging · License: MIT · Version: 1.0.0
Tags: Whisper, Speech Recognition, ASR, Multimodal, Multilingual, OpenAI, Speech-To-Text, Transcription, Translation, Audio Processing
When to use it
Transcribes and translates audio with OpenAI’s Whisper (openai-whisper Python package and whisper CLI), covering model sizes from tiny to large plus turbo, language specification, initial prompts, word and segment timestamps, temperature fallback, batch processing, and subtitle generation. Use when transcribing speech, podcasts, meetings, or video audio to text. Use when translating non-English speech to English. Use when working with noisy or multilingual audio in any of 99 languages. Use when choosing a Whisper model size for available VRAM. Use when generating subtitles from audio. Not for speaker diarization or live captioning; use AssemblyAI or Deepgram instead.Example requests
Ask your agent in plain language, for example:- “What’s the quickest way to transcribe an mp3 to text with Whisper on my laptop?”
- “I have 40 lecture recordings in ./lectures/.m4a, mostly Spanish with some English code-switching, and a 8 GB GPU. I ran
whisper lec01.m4a --model largeand got CUDA out of memory. How should I process the whole folder and get .srt subtitles for each?”* - “I recorded about 20 field interviews in Swahili and Tagalog on a noisy phone recorder. I need English text versions I can quote in my paper. What should I do, and what should I watch out for?”
Install
/plugin marketplace add KalarisLabs/research-agent-skills and install the whole multimodal-and-emerging category with /plugin install multimodal-and-emerging@research-agent-skills.