Whisper

Overview

Whisper is OpenAI's open-source automatic speech recognition model. It converts speech recordings into text and can also translate supported non-English speech into English. Developers use it as a building block for transcription applications, subtitle workflows, search, and accessibility tools. Because it is a model rather than a hosted consumer editor, users generally need a suitable runtime and technical setup.

What is Whisper?

Whisper is an automatic speech recognition system that turns recorded or live speech into text. It is commonly used by developers and technical users who need transcription that can run through code or locally rather than only through a hosted editor.

Its main value is speech recognition rather than podcast publishing or voice generation. The open-source release can be integrated into applications and workflows, but setup, compute requirements, model selection, and output cleanup remain the user's responsibility.

Key Features

• speech recognition
• multilingual transcription
• translation to English
• timestamped transcription
• multiple model sizes
• local deployment

Benefits

Faster audio production
Less repetitive manual processing
Easier experimentation
A workflow tailored to a specific audio task

Use Cases

• speech recognition
• Podcast or video production
• Educational audio
• Marketing and social content
• Developer or creator experiments

How to Use

1. Open the product
2. Choose the relevant audio workflow
3. Add the supported text, recording, prompt, or track
4. Generate or process the audio
5. Review pronunciation, artifacts, and timing
6. Export the result