NovaSR is an extremely lightweight and high-performance audio upsampling model that transforms low-quality 16 kHz audio into clearer, high-fidelity 48 kHz audio with remarkable speed and efficiency. At only about 50 KB in size, the model is orders of magnitude smaller than typical audio super-resolution networks, yet it achieves high quality and realtime performance thanks to its compact architecture and efficient convolutional design. NovaSR is especially valuable for post-processing tasks in speech enhancement, TTS pipelines, and dataset restoration where low sampling rates degrade perceived audio clarity; the minimal model size also makes it suitable for edge and embedded use cases where memory is at a premium. Its performance can reach thousands of times realtime on modern GPUs, allowing massive audio batches to be processed with negligible compute overhead.
Features
- Very small model size (~50 KB)
- Upsamples 16 kHz audio to 48 kHz
- Ultra-fast inference (thousands × realtime)
- Simple Python install and API
- Useful for TTS enhancement and dataset restoration
- Minimal resource requirements for edge use