podcast-generation

Generate podcast audio from text using WebSocket streaming by connecting a React frontend to a Python FastAPI backend, sending text scripts to Azure OpenAI Realtime Mini, and receiving base64-encoded audio chunks. The workflow converts PCM audio to WAV format at 24 kHz for real-time playback.

Text-to-speech podcast generation supports multiple voices including alloy, echo, and fable. Select a voice when providing your text script to generate streaming podcast audio accompanied by a real-time transcript of the spoken content.

Yes, Azure OpenAI Realtime Mini works with a Python FastAPI backend for audio streaming. The backend handles WebSocket connections, processes base64-encoded audio delivery, manages voice selection, and implements error handling for the end-to-end text-to-audio pipeline.

The podcast generation pipeline outputs standard WAV files by converting raw PCM audio to WAV format at a 24 kHz sample rate. Audio is delivered as base64-encoded data over WebSocket, enabling live audio output in the React frontend.

Text-to-audio streaming pipelines need WebSocket connections to enable end-to-end real-time audio delivery from Azure OpenAI Realtime Mini. WebSocket streaming reduces latency between content creation and audio playback, allowing the React frontend to receive live audio chunks and transcripts.

Real-time transcripts are available during AI podcast generation. As the Azure OpenAI Realtime Mini model streams base64-encoded audio over WebSocket, the pipeline simultaneously returns text transcripts, allowing the React frontend to display synchronized transcript content.