Applio vs DDSP-SVC
Applio
applio.orgDDSP-SVC
github.comSide by side
| Figure | Applio | DDSP-SVC |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | Yes | — |
| Web | Yes | — |
| Windows | Yes | Yes |
| macOS | Yes | — |
| Linux | Yes | — |
| API | Yes | — |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · AI voice changers | 9.1 (#3) | 7.8 (#41) |
| Spec score · AI song cover generators | 9.0 (#4) | 7.7 (#24) |
| Integrations | Official download materials link Google Colab, Pinokio and Hugging Face as cloud or one-click launch options. | The README recommends installing PyTorch and documents TensorBoard for viewing training status and generated test audio. |
| Model training | Users can preprocess datasets, extract features, train models and export them. | The project documents preprocessing audio datasets and training a model with a rectified-flow script. |
| What it does | Applio is an open-source AI voice-conversion suite for creating covers, training voice models and converting voices in real time. | DDSP-SVC is an open-source project for real-time singing voice conversion. |
Plans
In their own words
Applio
Applio is an open-source AI voice conversion suite for making covers, training custom voice models, and changing voices in real time. It can convert recorded audio with ready-made models, plus pitch tuning, cleanup, upscaling, and batch processing. Live conversion is intended for songs, streams, and calls. Model tools include training, a voice blender, text-to-speech, and an audio analyzer for dataset readiness. Applio supports Linux, macOS, Windows, web, and self-hosted use; Google Colab, Pinokio, and Hugging Face are also listed as ways to run it. Its plan is free, with no accounts or paywalls. The MIT license permits personal, research, and commercial use. The maker says audio and models remain on the device unless shared, and core features do not require an account, telemetry, or cloud dependency. Documentation recommends an Nvidia RTX 20-series GPU or newer for local voice training; most modern computers can handle inference with existing models.