Real-time voice streaming for AI agents with Kokoro TTS on SageMaker
In brief
- Kokoro-82M model (82M parameters) is deployed on SageMaker AI for streaming speech synthesis.
- Audio is generated sentence by sentence as soon as it's ready, reducing perceived latency.
- Two transport modes are offered: Server-Sent Events (SSE) or unified binary stream via WebSocket.
Amazon SageMaker AI now supports streaming speech synthesis for AI voice agents using the Kokoro-82M model. According to the announcement, this approach cuts perceived latency by starting synthesis as soon as the first sentence is available, rather than waiting for the full response.
The post outlines the technical setup: deploying a SageMaker endpoint hosting Kokoro-82M on an ml.g5.xlarge GPU instance, managing bidirectional WebSocket streams, and integrating with a Strands agent on Amazon Bedrock. Costs and performance are analyzed, including audio transport options (SSE or unified binary stream).
This solution targets production voice agents, focusing on response time reduction and inference cost optimization. Limitations include no concurrent synthesis and the need to adapt existing pipelines for binary streams.
What it changes for you
- Public SectorPublic services using voice agents can reduce user wait times with real-time speech synthesis.
This summary gives you the essentials. The full article, its figures and quotes are on Artificial Intelligence.
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