README.md

metadata

license: agpl-3.0
tags:
  - rknn

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

1. 克隆或者下载此仓库到瑞芯微SoC的系统上.

2. 安装依赖

pip install -r requirements.txt
pip install rknn-toolkit-lite2

4. 运行

python melotts_rknn.py -s "你想要生成的文本"

模型转换

1. 安装依赖

pip install -r requirements.txt
pip install rknn-toolkit2==2.3.0

2. 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

• melotts.axera
• MeloTTS

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

1. Clone or download this repository to your Rockchip SoC system.

2. Install dependencies

pip install -r requirements.txt
pip install rknn-toolkit-lite2

3. Run

python melotts_rknn.py -s "The text you want to generate."

Model Conversion

1. Install dependencies

pip install -r requirements.txt
pip install rknn-toolkit2==2.3.0

2. 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

• melotts.axera
• MeloTTS