openai-whisper-api

Audio transcription to text is automated by sending files like m4a, mp3, or ogg to OpenAI's Whisper-1 model. This eliminates manual transcription by processing speech directly through the API to output accurate text.

For speech-to-text conversion, the Whisper API supports common audio formats including m4a, mp3, and ogg. These files are processed directly to generate readable text or structured JSON transcripts.

Yes, a valid OPENAI_API_KEY is required to transcribe audio files. You can also optionally configure an OPENAI_BASE_URL to route API requests through a proxy or local gateway.

Yes, you can provide custom language hints and prompt guidance to improve speech-to-text transcription. This helps the Whisper model accurately recognize domain-specific terms, technical jargon, or speaker names during audio processing.

The best way to get structured JSON output from audio transcription is configuring the Whisper API to return JSON formats instead of plain text. This provides structured data for easier integration into meeting documentation or content workflows.

You can transcribe a long interview recording without manual typing by processing it through the OpenAI Whisper API. The speech-to-text model converts hour-long audio files in minutes, delivering text transcripts ready for editing.