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--- |
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license: agpl-3.0 |
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tags: |
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- rknn |
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--- |
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# MeloTTS-RKNN2 |
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## (English README see below) |
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在RK3588上运行MeloTTS文字转语音模型! |
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- 推理速度(RK3588): 约5倍速 |
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- 内存占用(RK3588): 约0.2GB |
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## 使用方法 |
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1. 克隆或者下载此仓库到瑞芯微SoC的系统上. |
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2. 安装依赖 |
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```bash |
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pip install -r requirements.txt |
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pip install rknn-toolkit-lite2 |
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``` |
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4. 运行 |
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```bash |
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python melotts_rknn.py -s "你想要生成的文本" |
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``` |
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## 模型转换 |
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1. 安装依赖 |
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```bash |
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pip install -r requirements.txt |
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pip install rknn-toolkit2==2.3.0 |
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``` |
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2. 转换模型 |
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```bash |
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python convert_rknn.py |
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``` |
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## 已知问题 |
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- 和原项目一样，Encoder部分并没有使用NPU加速，但是耗时不大，应该不会对推理速度有太大影响。 |
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## 参考 |
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- [melotts.axera](https://github.com/ml-inory/melotts.axera) |
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- [MeloTTS](https://github.com/myshell-ai/MeloTTS) |
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## English README |
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# MeloTTS-RKNN2 |
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Run the MeloTTS text-to-speech model on RK3588! |
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- Inference speed (RK3588): about 5x real-time |
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- Memory usage (RK3588): about 0.2GB |
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## Usage |
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1. Clone or download this repository to your Rockchip SoC system. |
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2. Install dependencies |
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```bash |
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pip install -r requirements.txt |
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pip install rknn-toolkit-lite2 |
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``` |
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3. Run |
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```bash |
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python melotts_rknn.py -s "The text you want to generate." |
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``` |
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## Model Conversion |
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1. Install dependencies |
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```bash |
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pip install -r requirements.txt |
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pip install rknn-toolkit2==2.3.0 |
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``` |
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2. Convert the model |
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```bash |
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python convert_rknn.py |
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``` |
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## Known Issues |
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- Same as the original project, the Encoder part is not accelerated by the NPU. However, its processing time is short and should not significantly affect the inference speed. |
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## References |
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- [melotts.axera](https://github.com/ml-inory/melotts.axera) |
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- [MeloTTS](https://github.com/myshell-ai/MeloTTS) |
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