Real-time Voice Activity Detection (VAD) Study Cases

This project focuses on Real-time Voice Activity Detection (VAD), enabling systems to detect when a user is speaking and when they are silent. By leveraging VAD, applications can achieve smarter, more human-like interactions through real-time speech analysis.

🔹 Key Features:

• Real-time VAD – Detects voice activity with low latency.
• Agent Interruption – Voice bots can gracefully stop talking when the user starts speaking.
• Seamless Integration – Works with speech-to-text pipelines for live transcription.
• Lightweight & Efficient – Optimized for real-time use cases.

🔹 Example Use Cases:

• Simple Voice Bot: A conversational AI agent that listens and responds naturally by detecting user speech in real time.
• Live Transcription (Real-time Transcription): Automatically captures speech-to-text while ignoring silence and background noise, making transcription more accurate and efficient.

Research and Prove of Concept - State of the Art 1

• VAD for Javascript: https://github.com/ricky0123/vad
• Docs: https://docs.vad.ricky0123.com/user-guide/api/
• Base Model VAD: https://github.com/snakers4/silero-vad
• Sample Video: Youtube: Demo Apps - SOA 1