OpenAI Realtime Speech-to-Speech
Configure OpenAI's realtime voice models for ultra-low latency, natural turn-taking, and human-like voice conversations. Combines speech recognition, language modeling, and voice synthesis into a single streaming session.
Lower Latency
Reduces delay between caller speech and response
Native Voice
Processes spoken interactions in real time
Better Interruptions
Handles caller interruptions more naturally
Streaming Responses
Begins speaking before full response is generated
What is it
OpenAI Realtime Speech-to-Speech
Traditional voice assistants use multiple independent systems — each introducing latency. OpenAI Realtime Speech-to-Speech combines speech recognition, language modeling, and voice synthesis into a single streaming model that can listen, reason, and respond in real time.
Traditional pipeline
Each stage adds latency before the caller hears a response.
Why use it
Fewer stages means faster, more natural calls
Realtime models reduce the number of processing stages required before a response can begin and support conversational turn-taking with fewer awkward pauses.
Faster Conversations
Reduces the number of processing stages before a response can begin.
More Natural Interactions
Supports conversational turn-taking with fewer awkward pauses.
Better Interruption Handling
Allows callers to interrupt naturally without breaking conversation flow.
Lower Pipeline Complexity
Fewer independent providers and services are required.
Best use cases
Where realtime models work best
Realtime models shine in conversational, turn-taking scenarios. They are less suited for workflows requiring structured data collection or exact transcript verification.
Recommended
- Receptionists
- Appointment booking
- Outbound sales
- Lead qualification
- Customer support
- Voice assistants
Not Recommended
- Heavy structured data collection
- Compliance-sensitive workflows
- Workflows requiring exact transcript verification
- Custom third-party TTS deployments