mirror of
https://github.com/storytold/storyteller-ml.git
synced 2026-10-22 08:16:08 +00:00
Justin John
73 lines
3.2 KiB
Markdown
73 lines
3.2 KiB
Markdown
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# GPT-SoVITS CLI
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This repository contains a command-line interface (CLI) script for the GPT-SoVITS project, which allows you to perform text-to-speech (TTS) synthesis using custom models.
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## Prerequisites
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- Docker
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## Setup
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### Build the Docker Image
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To build the Docker image, run the following command:
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```sh
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docker build --no-cache -t gpt-sovits:latest .
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```
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### Run the Docker Container
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To run the Docker container, use the following command:
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```sh
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docker run -it --privileged --gpus all gpt-sovits:latest
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```
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## Usage
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To run the CLI script, use the following command:
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```sh
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python fakeyou_infer.py [OPTIONS]
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```
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### Options
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- `--use_pretrained_gpt`: Use pretrained GPT model. If enabled, the script will use the default pretrained models for GPT and SoVITS.
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- `--use_pretrained_sovits`: Use pretrained SoVITS model. If enabled, the script will use the default pretrained models for GPT and SoVITS.
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- `--gpt_model`: Path to GPT model checkpoint. Required if `--use_pretrained_gpt` is not enabled.
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- `--sovits_model`: Path to SoVITS model checkpoint. Required if `--use_pretrained_sovits` is not enabled.
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- `--ref_audio`: Path to reference wav file. Required.
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- `--ref_text`: Path to reference text file (optional). If left blank \`""\` or not passed, it will disable the reference text and use the reference audio.
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- `--target_language`: Language of the target text. Choices: `chinese`, `english`, `japanese`, `chinese+english`, `japanese+english`, `automatic`.
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- `--ref_language`: Language of the reference text. Choices: `chinese`, `english`, `japanese`, `chinese+english`, `japanese+english`, `automatic`.
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- `--target_text`: Path to the target text file. Required.
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- `--how_to_cut`: How to cut the text for synthesis. Default: `No slice`. Options: `No slice`, `Slice once every 4 sentences`, `Cut per 50 characters`, `Slice by Chinese punct`, `Slice by English punct`, `Slice by every punct`.
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- `--top_k`: Top K sampling. Default: 20.
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- `--top_p`: Top P sampling. Default: 0.6.
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- `--temperature`: Sampling temperature. Default: 0.6.
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- `--speed`: Speed of the synthesized speech. Default: 1.0.
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- `--output_path`: Path to save the output wav file. Default: `output`.
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### Example Commands
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#### Using Custom Models with Reference Audio
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```sh
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python fakeyou_infer.py --gpt_model GPT_weights/your_gpt_model.ckpt --sovits_model SoVITS_weights/your_sovits_model.pth --ref_audio data/voice/sponge.wav --ref_text data/voice/ref.txt --target_text data/voice/input.txt --target_language english --ref_language english --how_to_cut "Slice once every 4 sentences" --speed 1.0 --output_path output/
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```
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#### Using Custom Models Without Reference Text
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```sh
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python fakeyou_infer.py --gpt_model GPT_weights/your_gpt_model.ckpt --sovits_model SoVITS_weights/your_sovits_model.pth --ref_audio data/voice/sponge.wav --target_text data/voice/input.txt --target_language english --ref_language english --how_to_cut "Slice once every 4 sentences" --speed 1.0 --output_path output/
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```
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#### Using Pretrained Models
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```sh
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python fakeyou_infer.py --use_pretrained_gpt --use_pretrained_sovits --ref_audio data/voice/sponge.wav --ref_text data/voice/ref.txt --target_text data/voice/input.txt --target_language english --ref_language english --how_to_cut "Slice once every 4 sentences" --speed 1.0 --output_path output/
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```
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