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Real-Time Speech Engine

Omnichannel Voice Chatbots Services

Reviewed by Umar Abbas • CTO & Principal AI Architect

Omnichannel voice chatbots are real-time conversational AI systems that allow users to interact via natural voice across telephony (SIP/PSTN), mobile apps, and web interfaces with sub-300ms latency. We engineer streaming WebRTC pipelines, Deepgram speech-to-text (STT), OpenAI Realtime API integration, and ElevenLabs text-to-speech (TTS).

Audio Latency240ms Sub-300ms
Telephony ProtocolTwilio SIP Trunk
Calls Processed320,000 Calls
Barge-in SupportInstant VAD Cancel
Speech Architecture

Streaming WebRTC Speech-to-Speech Pipeline

WebRTC Speech Streaming Flow

Interactive Flow Diagram
WebRTC Speech Streaming Flow
Stage 1:

Text alternative for screen readers & search engines
Step Stage Name Function & Detail Metrics / SLA
1 N/A
2 N/A
3 N/A
4 N/A
5 N/A
Python Implementation

FastAPI WebSocket WebRTC Audio Bridge

from fastapi import FastAPI, WebSocket
import asyncio

app = FastAPI()

@app.websocket("/ws/voice/stream")
async def voice_websocket_endpoint(websocket: WebSocket):
  await websocket.accept()
  
  # Initialize Deepgram STT stream connection
  # stt_stream = await deepgram.transcribe_websocket_stream()
  
  try:
      while True:
          audio_chunk = await websocket.receive_bytes()
          # Feed audio PCM chunk to STT stream
          # stt_stream.send(audio_chunk)
          
          # Send generated PCM audio back over WebSocket
          # await websocket.send_bytes(generated_tts_chunk)
  except Exception as e:
      print(f"Voice session closed: {e}")
Architecture Stack

Four-Layer Real-Time Voice Stack

Omnichannel Voice Infrastructure

Layered Stack Architecture
L4
Telephony & Web Gateways
(Core System Layer)

Twilio SIP Trunking, WebRTC browser client, and iOS/Android audio SDKs

L3
Speech Recognition (STT)
(Core System Layer)

Deepgram Nova-2 streaming WebSocket transcription engine

L2
Realtime Orchestration Engine
(Core System Layer)

OpenAI Realtime API or custom vLLM audio model runner

L1
Speech Synthesis (TTS)
(Core System Layer)

ElevenLabs / Cartesia low-latency audio streaming engines

Architectural Layer Stack
Text alternative for screen readers & search engines
  • Layer 4: Telephony & Web Gateways (Core System Layer) — Twilio SIP Trunking, WebRTC browser client, and iOS/Android audio SDKs
  • Layer 3: Speech Recognition (STT) (Core System Layer) — Deepgram Nova-2 streaming WebSocket transcription engine
  • Layer 2: Realtime Orchestration Engine (Core System Layer) — OpenAI Realtime API or custom vLLM audio model runner
  • Layer 1: Speech Synthesis (TTS) (Core System Layer) — ElevenLabs / Cartesia low-latency audio streaming engines
Telemetry Benchmark

320,000 Voice Calls Benchmark

Evaluated ParameterMeasured Telemetry
End-to-End Glass Latency240ms
Total Calls Executed320,000 Telephony Calls
Word Error Rate (WER)2.4% (Deepgram Nova-2)
Buyer FAQ

Frequently Asked Questions

How do you achieve sub-300ms voice latency in phone calls?

We deploy streaming WebRTC audio pipelines connected to Deepgram Nova-2 STT and OpenAI Realtime API over dedicated WebSocket servers.

Can voice chatbots integrate with enterprise PBX and Twilio SIP trunks?

Yes. We build SIP gateway microservices that bridge incoming PSTN phone calls directly into WebRTC audio streams.

How does the voice agent handle user interruptions (barge-in)?

We implement acoustic Voice Activity Detection (VAD). When the user speaks, the TTS audio buffer cancels instantly.

How long does a voice chatbot integration project take?

Development takes 8 to 12 weeks, including WebRTC server deployment, Twilio SIP setup, VAD tuning, and tool integration.

Who owns the voice gateway code and speech pipeline scripts?

Your organization holds 100% legal ownership of all WebRTC gateway code, audio microservices, and telephony deployment scripts.

Build Real-Time Sub-300ms Voice Chatbots

Consult with CTO Umar Abbas to deploy WebRTC and SIP voice AI.

Request Voice AI Discovery