building speech segmentation heuristics with silero vad

[lukeocodes]

Integration: Silero VAD Speech Segmentation with Deepgram STT

What this should show

A Python example demonstrating how to use Silero VAD (Voice Activity Detection) to segment audio into speech regions, then send those segments to Deepgram STT for transcription. This covers a common pre-processing pipeline: detect speech boundaries with Silero VAD, extract speech segments, and transcribe each segment with Deepgram.

Key features to demonstrate:

• Loading and running the Silero VAD model (via torch or silero-vad package)
• Processing audio to detect speech vs. silence boundaries
• Applying segmentation heuristics (min speech duration, min silence gap, padding)
• Sending detected speech segments to Deepgram for transcription
• Reconstructing a timeline of transcribed segments

Credentials likely needed

• DEEPGRAM_API_KEY (Silero VAD runs locally, no additional API key needed)

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Original request:

What's on your mind?

building speech segmentation heuristics with silero vad

Any extra context? (optional)

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[github-actions]

Ooo, we'll get right on that! 🎉

The Engineer will pick this up shortly and build a Silero VAD speech segmentation + Deepgram STT example in Python — showing how to detect speech boundaries locally with Silero VAD and then transcribe each segment with Deepgram.

I'll keep this issue open so you can track progress — we'll close it automatically when the PR merges.

If you have any extra context (preferred language, specific VAD settings, or whether you want real-time streaming vs. file-based processing), drop it here — it helps the build go faster!

[github-actions]

Built in #208