Real-Time Speech Streaming Kyutai STT Live Transcription with AI in Free Colab
AI Summary
This video provides an end-to-end demonstration of Kyoai’s newly released speech-to-text (ST) model featuring a semantic voice activity detection (VAD) system. The presenter shows how to install and run the model in a free Google Colab environment for real-time streaming from a local microphone. The semantic VAD intelligently detects when a user has completed their spoken request, improving natural speech handling compared to traditional VADs which struggle with pauses and hesitations. The video includes a live transcription demo with impressive accuracy, explains the underlying transformer-based architecture, model parameters (1B bilingual and 2.6B English-only versions), and training data (2.5M hours of audio). The presenter also describes the code setup involving microphone capture in the browser, audio preprocessing, and PyTorch-based transcription pipeline. Finally, there’s a nod to the sponsor Camel AI, an open-source community focused on multi-agent infrastructures. The presenter encourages viewers to support the channel for access to the code.