Merge pull request #71 from lfchener/readme

add README for tacotron2

examples/tacotron2/README.md

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+# Tacotron2
+
+PaddlePaddle dynamic graph implementation of Tacotron2, a neural network architecture for speech synthesis directly from text. The implementation is based on [Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions](https://arxiv.org/abs/1712.05884).
+
+## Project Structure
+
+```text
+├── config.py              # default configuration file
+├── ljspeech.py            # dataset and dataloader settings for LJSpeech
+├── preprocess.py          # script to preprocess LJSpeech dataset
+├── synthesis.py           # script to synthesize spectrogram from text
+├── train.py               # script for tacotron2 model training
+```
+
+## Dataset
+
+We experiment with the LJSpeech dataset. Download and unzip [LJSpeech](https://keithito.com/LJ-Speech-Dataset/).
+
+```bash
+wget https://data.keithito.com/data/speech/LJSpeech-1.1.tar.bz2
+tar xjvf LJSpeech-1.1.tar.bz2
+```
+
+Then you need to preprocess the data by running ``preprocess.py``, the preprocessed data will be placed in ``--output`` directory.
+
+```bash
+python preprocess.py \
+--input=${DATAPATH} \
+--output=${PREPROCESSEDDATAPATH} \
+-v  \
+```
+
+For more help on arguments
+
+``python preprocess.py --help``.
+
+## Train the model
+
+Tacotron2 model can be trained by running ``train.py``.
+
+```bash
+python train.py \
+--data=${PREPROCESSEDDATAPATH} \
+--output=${OUTPUTPATH} \
+--device=gpu \
+```
+
+If you want to train on CPU, just set ``--device=cpu``.
+If you want to train on multiple GPUs, just set ``--nprocs`` as num of GPU.
+By default, training will be resumed from the latest checkpoint in ``--output``, if you want to start a new training, please use a new ``${OUTPUTPATH}`` with no checkpoint. And if you want to resume from an other existing model, you should set ``checkpoint_path`` to be the checkpoint path you want to load.
+
+**Note: The checkpoint path cannot contain the file extension.**
+
+For more help on arguments
+
+``python train_transformer.py --help``.
+
+## Synthesis
+
+After training the Tacotron2, spectrogram can be synthesized by running ``synthesis.py``.
+
+```bash
+python synthesis.py \
+--config=${CONFIGPATH} \
+--checkpoint_path=${CHECKPOINTPATH} \
+--input=${TEXTPATH} \
+--output=${OUTPUTPATH}
+--device=gpu
+```
+
+The ``${CONFIGPATH}`` needs to be matched with ``${CHECKPOINTPATH}``.
+
+For more help on arguments
+
+``python synthesis.py --help``.
+
+Then you can find the spectrogram files in ``${OUTPUTPATH}``, and then they can be the input of vocoder like [waveflow](../waveflow/README.md#Synthesis) to get audio files.