For users in China region, you can use AutoDL Cloud Docker to experience the full functionality online: https://www.codewithgpu.com/i/RVC-Boss/GPT-SoVITS/GPT-SoVITS-Official
## Features:
1. **Zero-shot TTS:** Input a 5-second vocal sample and experience instant text-to-speech conversion.
2. **Few-shot TTS:** Fine-tune the model with just 1 minute of training data for improved voice similarity and realism.
@ -92,7 +91,6 @@ Download and place [ffmpeg.exe](https://huggingface.co/lj1995/VoiceConversionWeb
### Pretrained Models
Download pretrained models from [GPT-SoVITS Models](https://huggingface.co/lj1995/GPT-SoVITS) and place them in `GPT_SoVITS/pretrained_models`.
For UVR5 (Vocals/Accompaniment Separation & Reverberation Removal, additionally), download models from [UVR5 Weights](https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main/uvr5_weights) and place them in `tools/uvr5/uvr5_weights`.
@ -105,9 +103,10 @@ Users in China region can download these two models by entering the links below
For Chinese ASR (additionally), download models from [Damo ASR Model](https://modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/files), [Damo VAD Model](https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/files), and [Damo Punc Model](https://modelscope.cn/models/damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch/files) and place them in `tools/damo_asr/models`.
### For Mac Users
If you are a Mac user, make sure you meet the following conditions for training and inferencing with GPU:
If you are a Mac user, make sure you meet the following conditions for training and inferencing with GPU:
- Mac computers with Apple silicon or AMD GPUs
- macOS 12.3 or later
- Xcode command-line tools installed by running `xcode-select --install`
@ -115,12 +114,16 @@ If you are a Mac user, make sure you meet the following conditions for training
0. Regarding image tags: Due to rapid updates in the codebase and the slow process of packaging and testing images, please check [Docker Hub](https://hub.docker.com/r/breakstring/gpt-sovits) for the currently packaged latest images and select as per your situation, or alternatively, build locally using a Dockerfile according to your own needs.
1. Environment Variables:
- is_half: Controls half-precision/double-precision. This is typically the cause if the content under the directories 4-cnhubert/5-wav32k is not generated correctly during the "SSL extracting" step. Adjust to True or False based on your actual situation.
- is_half: Controls half-precision/double-precision. This is typically the cause if the content under the directories 4-cnhubert/5-wav32k is not generated correctly during the "SSL extracting" step. Adjust to True or False based on your actual situation.
2. Volumes Configuration,The application's root directory inside the container is set to /workspace. The default docker-compose.yaml lists some practical examples for uploading/downloading content.
3. shm_size: The default available memory for Docker Desktop on Windows is too small, which can cause abnormal operations. Adjust according to your own situation.
4. Under the deploy section, GPU-related settings should be adjusted cautiously according to your system and actual circumstances.
#### Running with docker compose
```
docker compose -f "docker-compose.yaml" up -d
```
@ -148,11 +152,11 @@ docker compose -f "docker-compose.yaml" up -d
#### Running with docker command
As above, modify the corresponding parameters based on your actual situation, then run the following command:
中国語 ASR(追加)については、[Damo ASR Model](https://modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/files)、[Damo VAD Model](https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/files)、[Damo Punc Model](https://modelscope.cn/models/damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch/files) からモデルをダウンロードし、`tools/damo_asr/models` に置いてください。