@@ -4,39 +4,6 @@ Paddle implementation of deepvoice 3 in dynamic graph, a convolutional network b
We implement Deepvoice 3 in paddle fluid with dynamic graph, which is convenient for flexible network architectures.
## Installation
### Install paddlepaddle.
This implementation requires the latest develop version of paddlepaddle. You can either download the compiled package or build paddle from source.
1. Install the compiled package, via pip, conda or docker. See [**Installation Mannuals**](https://www.paddlepaddle.org.cn/documentation/docs/en/beginners_guide/install/index_en.html) for more details.
2. Build paddlepaddle from source. See [**Compile From Source Code**](https://www.paddlepaddle.org.cn/documentation/docs/en/beginners_guide/install/compile/fromsource_en.html) for more details. Note that if you want to enable data parallel training for multiple GPUs, you should set `-DWITH_DISTRIBUTE=ON` with cmake.
### Install parakeet
You can choose to install via pypi or clone the repository and install manually.
1. Install via pypi.
```bash
pip install paddle-parakeet
```
2. Install manually.
```bash
git clone <url>
cd Parakeet/
pip install-e .
```
### Download cmudict for nltk
You also need to download cmudict for nltk, because convert text into phonemes with `cmudict`.
```python
importnltk
nltk.download("punkt")
nltk.download("cmudict")
```
## Dataset
We experiment with the LJSpeech dataset. Download and unzip [LJSpeech](https://keithito.com/LJ-Speech-Dataset/).