whisper

To transcribe audio to text in Python, use the openai-whisper library to load a speech recognition model and run it on your audio file, generating accurate text output across 99 languages.

Yes, speech recognition with Whisper supports auto language detection for transcription and can optionally translate the detected audio content into English using its unified multilingual model.

The best way to generate podcast transcription or meeting notes is applying a speech recognition model to the audio, where selecting larger model sizes increases accuracy for complex multilingual media processing.

Yes, multilingual speech recognition is natively supported, allowing you to process audio across 99 languages through auto language detection or by explicitly specifying the language for accurate transcription.

Choosing model sizes from tiny to large lets you balance transcription speed and accuracy, where smaller models process audio faster while larger models deliver higher precision for complex speech recognition tasks.

Specifying a language explicitly during audio processing bypasses auto detection overhead and ensures the speech recognition model targets the correct linguistic patterns for accurate multilingual transcription.