Voice Bot Barge-In & Latency Fix

Budget: ₹600 - ₹1500

I have a production-ready, end-to-end voice bot running on Plivo with a streaming pipeline that chains Deepgram for STT, an LLM for intent generation, and a TTS engine for playback. Two problems are stopping me from going live:

• Interruption handling (barge-in)

• when a caller begins speaking, the TTS stream should halt instantly, but today the audio keeps playing. • Latency
• the STT → LLM → TTS round-trip is a few seconds too slow; I need it trimmed to near real-time. • Overall flow optimisation
• once the first two points are stable, I’d like a quick sanity check on buffer sizes, chunk timing and any other easy wins.

I already have partial barge-in logic coded, yet it isn’t firing reliably, so I’m looking for a fresh set of eyes. The engagement is a focused 1-to-2-hour screen-share session where we step through my python code, inspect WebSocket packet flow, and patch the issues live.

By the end of the call I expect:

1. Clean, verifiable barge-in behaviour (caller speech immediately cancels TTS).
2. Measurable latency reduction in the streaming path.
3. A concise summary of any further tweaks I can apply after the session.

If you have hands-on experience with Plivo streams, Deepgram’s real-time API, and low-latency audio pipelines, let’s get this scheduled.