English

Low-latency Real-time Voice Conversion on CPU

Sound 2023-11-03 v1 Machine Learning Audio and Speech Processing

Abstract

We adapt the architectures of previous audio manipulation and generation neural networks to the task of real-time any-to-one voice conversion. Our resulting model, LLVC (L\textbf{L}ow-latency L\textbf{L}ow-resource V\textbf{V}oice C\textbf{C}onversion), has a latency of under 20ms at a bitrate of 16kHz and runs nearly 2.8x faster than real-time on a consumer CPU. LLVC uses both a generative adversarial architecture as well as knowledge distillation in order to attain this performance. To our knowledge LLVC achieves both the lowest resource usage as well as the lowest latency of any open-source voice conversion model. We provide open-source samples, code, and pretrained model weights at https://github.com/KoeAI/LLVC.

Keywords

Cite

@article{arxiv.2311.00873,
  title  = {Low-latency Real-time Voice Conversion on CPU},
  author = {Konstantine Sadov and Matthew Hutter and Asara Near},
  journal= {arXiv preprint arXiv:2311.00873},
  year   = {2023}
}

Comments

8 pages, 2 figures

R2 v1 2026-06-28T13:09:07.258Z