OpenAI Whisper Speech Recognition Guide
Official documentation for OpenAI Whisper, the open-source speech recognition model trained on diverse multilingual audio. It covers installation, model size selection, and transcription API usage, with support for roughly 99 languages and direct translation to English. Aimed at developers who need accurate, locally runnable speech-to-text for subtitling, meeting notes, or voice search indexing.
Overview
"OpenAI Whisper Speech Recognition Guide" is a "Guide" resource curated by AI Resource Hub, filed under the Tutorial Resources category and suited to Intermediate-level learners. It is provided by OpenAI, was last updated on 2026-06-16, and holds an editorial score of 4.5/5 from our team. Click "Visit Resource" on the right to open the original page.
Our Verdict
This guide does what a Whisper guide should: walk you from zero to working transcription via both the hosted API and the local open-source path, so you can trade convenience against privacy. Its model-size and language guidance is genuinely practical — small or base for clean English, bigger models for accents, noise, and other languages. Expectations, honestly: the hosted API is billed, large models want a GPU, and strong accents or background noise still cost accuracy. Developers building subtitling, meeting notes, or voice search should start here.
Tags
Key Features
- ▹Step-by-step transcription with Whisper
- ▹Covers both the API and local usage
- ▹Tips for formats and languages
Pros
- +Hands-on and practical
- +Covers API and local paths
- +Covers both the hosted API and local open-source Whisper
Cons
- −Hosted API usage is billed
- −Larger local models need a GPU for speed
- −Accuracy drops on heavy accents or noise
FAQ
Details
- Pricing
- Free guide (Whisper API is usage-based)
- Author
- OpenAI
- Editorial score
- ★ 4.5 / 5
- Last updated
- Jun 16, 2026