This is a submission for the AssemblyAI Challenge: Really Rad Real-Time.
What I Built
I built a sophisticated speech-to-text application utilizing AssemblyAI's Universal-2 model. This application provides real-time transcription, speaker diarization, and highlight extraction using AssemblyAI's advanced APIs. It's designed for scenarios like meetings, conferences, and interviews where accurate transcription with speaker attribution is essential.
Key Features:
- Real-time Transcription: Captures audio from a microphone and provides a live transcription of the conversation.
Screenshots
Main Interface:
Journey
I implemented AssemblyAI's Streaming API to bring real-time transcription to life. Here are the steps I followed:
Backend Setup: I set up an Express server to manage WebSocket connections, allowing the app to send audio data to AssemblyAI's streaming endpoint.
Frontend Integration: Using React, I built a user-friendly interface that lets users start and stop transcriptions. I used Socket.IO to handle communication between the client and server.
AssemblyAI Integration: I utilized AssemblyAI’s SDK to connect my application to the Universal-2 model. I configured the API to support speaker diarization and highlights.
Challenges Faced:
Understanding the WebSocket integration was challenging, but the AssemblyAI documentation provided valuable guidance.
Fine-tuning the real-time aspects of the application was also tricky, particularly with managing data flow between the backend and frontend efficiently.
Installation Instructions
- Clone the Repository:
bash
git clone https://github.com/DesignByDevDan/AssemblyAI-Challenge.git
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