AWS Announces Real-Time Personalized Speech Deployment with Qwen3-TTS
AWS has introduced the capability to deploy the Qwen3-TTS-12Hz-1.7B-Base text-to-speech model on Amazon SageMaker AI for real-time personalized speech generation.
AWS has announced the deployment of the Qwen3-TTS-12Hz-1.7B-Base text-to-speech model on Amazon SageMaker AI, enabling real-time personalized speech generation. This capability allows users to generate new speech in a target speaker’s voice from a short reference recording without retraining the model. The model can be used by media teams, educators, and application developers to create personalized voice experiences and localize multilingual content. Additionally, it supports accessible communication and preserves a speaker’s identity across languages. With Amazon SageMaker AI, users can deploy the model on a fully managed real-time inference endpoint, handling infrastructure provisioning, health monitoring, and automatic scaling without managing underlying GPU servers. The deployment process is detailed in a technical guide, including the use of the Amazon SageMaker Python SDK and Amazon CloudWatch metrics for monitoring and optimization.
Source: aws-ml
