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Cartesia 在 AWS 上构建超低延迟语音 AI 应用

Building ultra-low-latency voice AI applications on AWS

官方一手AWS Machine Learning Blog@Nolan Chen
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Why we picked it

Cartesia 的 Sonic 模型延迟低于 100ms，这篇 AWS 教程手把手教你在 SageMaker 或 EC2 上部署，做语音应用可以照着抄。

AWS 发布教程，介绍合作伙伴 Cartesia 如何用 State Space Models 实现低于 100ms 延迟的文本转语音和语音转文本。文章演示了通过 Amazon SageMaker AI 部署 Cartesia 的 Sonic 模型的具体步骤。另一种方案是在 Amazon EC2 GPU 实例上自行托管，适合需要更多控制权的团队。内容覆盖从模型选择到全球规模化部署的完整流程。

Image · AWS Machine Learning Blog
Original · AWS Machine Learning Blog

Building ultra-low-latency voice AI applications on AWS

Learn how Cartesia, an AWS Partner, uses purpose-built State Space Models and AWS infrastructure to deliver sub-100ms text-to-speech and speech-to-text at global scale, and how to deploy its Sonic model on Amazon SageMaker AI or self-managed Amazon EC2 GPU instances.

#Cartesia#Sonic#AWS#SageMaker#语音识别

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