> ## Documentation Index
> Fetch the complete documentation index at: https://notes.kodekloud.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Section Intro

> OpenAI Whisper is a Foundation Model for audio transcription and real-time speech translation with a simple API interface.

OpenAI Whisper is a powerful Foundation Model optimized for high-precision audio transcription and real-time speech translation. Whether you want to convert spoken content into text or translate non-English audio into English, Whisper delivers with a straightforward API interface.

## Key Capabilities

| Capability    | Description                                                                                    |
| ------------- | ---------------------------------------------------------------------------------------------- |
| Transcription | Convert spoken content from supported formats (e.g., MP3, WAV, FLAC) into written text.        |
| Translation   | Transcribe audio recorded in a foreign language and translate the resulting text into English. |

<Callout icon="lightbulb" color="#1CB2FE">
  Whisper supports multiple audio formats and language pairs out of the box. For optimal accuracy, use audio files encoded at 16 kHz.
</Callout>

In this lesson, we’ll walk through:

1. Uploading an audio file to the Whisper API
2. Invoking the transcription endpoint
3. Processing and analyzing the transcription result
4. Translating non-English audio into English

Let’s get started!

<CardGroup>
  <Card title="Watch Video" icon="video" cta="Learn more" href="https://learn.kodekloud.com/user/courses/mastering-generative-ai-with-openai/module/574a8a5c-b7a8-4902-aa33-c26eff12ee0b/lesson/ab7f7485-f6f2-47ff-a7d7-bf5a877ffa95" />
</CardGroup>