# Amazon — Stream low-latency speech from AI agents using Kokoro TTS on Amazon SageMaker AI

- Company: Amazon (amazon.com)
- Announced: 2026-10-22T17:45:58+00:00
- Category: not stated
- Coverage: not counted
- Announcement: no
- Group: routine
- Source: https://aws.amazon.com/blogs/machine-learning/stream-low-latency-speech-from-ai-agents-using-kokoro-tts-on-amazon-sagemaker-ai/
- Record: https://forck.live/items/26789-stream-low-latency-speech-from-ai-agents-using-kokoro-tts-on-amazon-sagemaker-ai
- Subject: Bedrock / Nova
- Models affected: Kokoro-82M

Amazon's guide shows how to stream each sentence from an AI agent to a hosted Kokoro-82M text-to-speech model on SageMaker AI, so audio starts before the full answer is written. The problem it addresses is the silence a caller hears while a text-to-speech integration waits for a long, multi-paragraph response to finish generating. Kokoro-82M has 82 million parameters, small enough to run cheaply on a single mid-tier GPU instance, which the guide says keeps latency and inference cost low for a voice agent handling real traffic. The model runs in a custom container on a SageMaker AI real-time endpoint on an ml.g5.xlarge instance, exposing a POST route for one complete input and a WebSocket route that holds one connection open across many messages. The walkthrough deploys the endpoint and the Amazon Bedrock AgentCore runtime hosting a Strands agent through two CLI tools, each wrapping its own AWS CDK stacks, and the endpoint must be deployed first. It also covers two client-side fixes: SageMaker AI delivers every part of a message as a binary WebSocket frame, so a handler calling receive_text() fails on every request, and the session must stay open between messages. The sample container pins an older PyTorch with a known advisory, PYSEC-2026-2286, fixed in torch 2.10.0, which the guide says should be reviewed and upgraded before any non-proof-of-value use.

## Evidence

Verbatim from https://aws.amazon.com/blogs/machine-learning/stream-low-latency-speech-from-ai-agents-using-kokoro-tts-on-amazon-sagemaker-ai/:

> This post shows how to close that gap. We stream each sentence to a hosted Kokoro-82M text-to-speech (TTS) model on Amazon SageMaker AI as soon as an agent produces it, so synthesis begins on sentence one instead of the finished response.

---

Record: https://forck.live/items/26789-stream-low-latency-speech-from-ai-agents-using-kokoro-tts-on-amazon-sagemaker-ai
Catalogue: https://forck.live/llms.txt
Current issue: https://forck.live/feed.md