Singularity in melody and content while transforming one singer’s voice into another’s has long been a challenge in singing voice conversion (SVC) technology. The slow processing speeds of diffusion-based SVC methods have hindered the real-time application of this technology, despite their ability to produce high-quality and natural audio.
A recent breakthrough, however, has emerged in the form of CoMoSVC, a new method developed by the Hong Kong University of Science and Technology and Microsoft Research Asia. CoMoSVC leverages the consistency model to achieve both high-quality audio generation and rapid sampling simultaneously.
CoMoSVC operates through a two-stage process: encoding and decoding. In the encoding stage, features are extracted from the waveform, and the singer’s identity is encoded into embeddings. The decoding stage is where CoMoSVC truly stands out. It uses these embeddings to generate mel-spectrograms, which are then transformed into audio. The key innovation lies in CoMoSVC’s student model, distilled from a pre-trained teacher model, enabling rapid, one-step audio sampling without compromising audio quality.
Performance evaluations have shown that CoMoSVC significantly outperforms state-of-the-art diffusion-based SVC systems in terms of inference speed, up to 500 times faster. Furthermore, it maintains or surpasses their audio quality, making it a groundbreaking development in the field. This balance between speed and quality opens up new possibilities for real-time and efficient voice conversion applications, with potential applications in music entertainment and beyond.
In conclusion, CoMoSVC represents a significant milestone in singing voice conversion technology. By addressing the critical issue of slow inference speed without compromising audio quality, it sets a new standard in the field. This breakthrough paves the way for revolutionary applications and advancements, marking a significant step forward in SVC technology.
The source of the article is from the blog mivalle.net.ar