The diagram illustrates how Bhashini.ai’s Streaming Speech-to-Text (STT) and Text-to-Speech (TTS) WebSocket APIs integrate into a modern AI-driven call center, enabling low-latency, full-duplex voice automation.
A Caller / End User initiates a voice call using a regular telephone or VoIP client. The call traverses the PSTN or VoIP network, ensuring compatibility with traditional telephony infrastructure.
The call is terminated at a Media Gateway, which can be:
An on-premise SIP PBX such as Asterisk
A cloud telephony provider like Twilio
A WebRTC platform such as LiveKit
The Media Gateway is responsible for:
SIP signaling
RTP audio handling
Bridging telephony audio to WebSocket-based AI services
This layer enables seamless integration between telecom networks and real-time AI pipelines.
The Media Gateway streams raw audio to Bhashini.ai Streaming STT using a low-latency WebSocket API.
Key capabilities of Bhashini STT:
Real-time streaming transcription
Built-in Voice Activity Detection (VAD)
Automatic speech segmentation
Interim (partial) and final transcripts
Optimized for conversational latency
Transcribed text (both interim and final) is forwarded to the LLM / Dialog Engine as soon as it becomes available, allowing the AI system to prepare the response while the caller is still speaking.
The LLM or Dialog Engine acts as the brain of the AI call center. It:
Maintains conversation context
Applies business logic and policies
Performs intent detection and slot filling
Invokes tools and APIs
When needed, it interacts with Enterprise Backend Systems such as:
CRM platforms
Ticketing systems
Payment gateways
Knowledge bases
This allows the AI agent to provide personalized, actionable responses in real time.
Once the LLM generates a response, text is sent to Bhashini.ai Streaming TTS via WebSocket.
Key TTS capabilities:
Low-latency, streaming audio synthesis
Natural, expressive voices
Optimized for conversational turn-taking
Suitable for barge-in and interruptions
Synthesized speech is streamed back to the Media Gateway, which injects it into the live call using RTP. The audio then flows through the PSTN/VoIP network and is played back to the caller.
Together, Streaming STT and Streaming TTS enable full-duplex voice bots, where:
The caller can speak at any time
The AI can respond incrementally
Latency is minimized to human-like levels
This architecture supports advanced use cases such as:
Automated IVRs
AI voice agents
Hybrid AI + human call centers
Multilingual customer support for Indian languages
Telephony-agnostic: Works with SIP, WebRTC, and cloud telephony
Low latency: Designed for real-time conversations
Scalable: Stateless WebSocket APIs fit cloud-native deployments
Composable: STT, LLM, and TTS are loosely coupled
Production-ready: Built for call-center workloads