LuxTTS Delivers Lightweight, Open-Source Speech Synthesis
The new text-to-speech model is optimized for the ONNX runtime, making it a promising option for efficient, on-device audio generation.
A new open-source text-to-speech (TTS) model called LuxTTS has been released by developer Yatharth Singh of the OpenMOSS community. Designed to be lightweight and efficient, it offers a new option for developers looking to generate English speech without relying on large, cloud-based APIs.
The model’s key feature is its optimization for the ONNX (Open Neural Network Exchange) runtime. This focus on a standardized format makes LuxTTS particularly well-suited for applications that need to run on-device or on resource-constrained hardware, where performance and low overhead are critical. Its permissive Apache 2.0 license also allows for broad use, including in commercial projects.
While many state-of-the-art speech models require significant computational power, LuxTTS prioritizes accessibility and practicality. By building for ONNX, the project aims to simplify deployment across various platforms, from desktop to mobile and edge devices. Developers can find the model, usage instructions, and inference code available now on the Hugging Face Hub.
LuxTTS joins a growing ecosystem of smaller, specialized open-source models that serve specific needs within the AI community. Its release provides a valuable, permissively licensed tool for developers who require local, efficient speech synthesis in their applications.
Sources
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YatharthS/LuxTTS
Hugging Face
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