Retrieval-based Voice Conversion
Retrieval-based Voice Conversion is a topic that has captured the attention of millions of people around the world. With a long history and significant impact on society, Retrieval-based Voice Conversion has been the subject of debate, study and research for decades. In this article, we will explore in detail the most relevant aspects related to Retrieval-based Voice Conversion, analyzing its importance, influence and possible implications for the future. From its origin to its current evolution, Retrieval-based Voice Conversion is a topic that continues to generate interest and curiosity, and it is crucial to understand its scope to better understand the world around us.
| Developer(s) | RVC-Project team |
|---|---|
| Initial release | 2023 |
| Repository | Github |
| Written in | Python |
| Operating system | Windows, Linux, macOS |
| Available in | English, Simplified Chinese, Japanese, Korean, French, Turkish, Portuguese |
| Type | Voice conversion software |
| License | MIT License |
Retrieval-based Voice Conversion (RVC) is an open source voice conversion AI algorithm that enables realistic speech-to-speech transformations, accurately preserving the intonation and audio characteristics of the original speaker.[1]
Overview
In contrast to text-to-speech systems such as ElevenLabs, RVC differs by providing speech-to-speech outputs instead. It maintains the modulation, timbre and vocal attributes of the original speaker, making it suitable for applications where emotional tone is crucial.
The algorithm enables both pre-processed and real-time voice conversion with low latency. This real-time capability marks a significant advancement over previous AI voice conversion technologies, such as So-vits SVC. Its speed and accuracy have led many to note that its generated voices sound near-indistinguishable from "real life", provided that sufficient computational specifications and resources (e.g., a powerful GPU and ample RAM) are available when running it locally and that a high-quality voice model is used. [2][3][4]
Applications and concerns
The technology enables voice changing and mimicry, allowing users to create accurate models of others using only a negligible amount of minutes of clear audio samples. These voice models can be saved as .pth (PyTorch) files. While this capability facilitates numerous creative applications, it has also raised concerns about potential misuse as deepfake software for identity theft and malicious impersonation through voice calls.
In pop culture
RVC inference has been used to create realistic depictions of song covers, such as replacing original vocals with characters like Twilight Sparkle and Mordecai to have them sing duets of popular music like "Airplanes" and "Somebody That I Used to Know." These AI-generated covers, which can sound strikingly similar to the voice imitated, have gained popularity on platforms like YouTube as humorous memes.[5]
References
- ^ Cochard, David (January 7, 2024). "RVC: An AI-Powered Voice Changer". Medium.
- ^ "What's RVC". AI Hub. Retrieved 2024-05-27.
- ^ Masuda, Naotake (September 21, 2023). "State-of-the-art Singing Voice Conversion methods". Medium.
- ^ "Understanding RVC - Retrieval-based Voice Conversion". Retrieved 2024-10-23.
- ^ "RVC WebUI How To – Make AI Song Covers in Minutes! (Voice Conversion Guide) - Tech Tactician". Tech Tactician. 2023-07-06. Retrieved 2024-05-27.
