MeloTTS-RKNN2
(English README see below)
在RK3588上运行MeloTTS文字转语音模型!
- 推理速度(RK3588): 约5倍速
- 内存占用(RK3588): 约0.2GB
使用方法
克隆或者下载此仓库到瑞芯微SoC的系统上.
安装依赖
pip install -r requirements.txt
pip install rknn-toolkit-lite2
- 运行
python melotts_rknn.py -s "你想要生成的文本"
模型转换
- 安装依赖
pip install -r requirements.txt
pip install rknn-toolkit2==2.3.0
- 转换模型
python convert_rknn.py
已知问题
- 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。
参考
English README
MeloTTS-RKNN2
Run the MeloTTS text-to-speech model on RK3588!
- Inference speed (RK3588): about 5x real-time
- Memory usage (RK3588): about 0.2GB
Usage
Clone or download this repository to your Rockchip SoC system.
Install dependencies
pip install -r requirements.txt
pip install rknn-toolkit-lite2
- Run
python melotts_rknn.py -s "The text you want to generate."
Model Conversion
- Install dependencies
pip install -r requirements.txt
pip install rknn-toolkit2==2.3.0
- Convert the model
python convert_rknn.py
Known Issues
- 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.
References
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