The integration of real-time transcription with Retrieval-Augmented Generation (RAG) is revolutionizing how we interact with AI-powered applications. By providing users with accurate, real-time transcriptions and generating context-aware responses to queries, you can deliver a dynamic and highly personalized experience.
In this blog, we’ll walk through building a real-time transcription app using MediaRecorder and the Azure Streaming API and explore how to enhance it with RAG functionality. We’ll also discuss the potential of using alternative generative models to OpenAI for query response generation, offering more flexibility and control.
Real-Time Transcription: How It Works
The transcription part of the app involves capturing audio in real-time using the MediaRecorder API in the browser and then streaming this audio to the Azure Streaming API for transcription. This setup ensures that users receive transcriptions as they speak, with minimal delay.