update pre-trained models with audio demos

Author: keonlee9420

README.md

@@ -24,11 +24,11 @@ pip3 install -r requirements.txt
 
 ## Inference
 
-You have to download the [pretrained models]() and put them in ``output/ckpt/LJSpeech/``.
+You have to download the [pretrained models](https://drive.google.com/drive/folders/1BBuaoSlInwFoUt1PKLxo0Sjl5qWCq945?usp=sharing) and put them in ``output/ckpt/LJSpeech/``.
 
 For English single-speaker TTS, run
 ```
-python3 synthesize.py --text "YOUR_DESIRED_TEXT" --restore_step 900000 --mode single -p config/LJSpeech/preprocess.yaml -m config/LJSpeech/model.yaml -t config/LJSpeech/train.yaml
+python3 synthesize.py --text "YOUR_DESIRED_TEXT" --restore_step 160000 --mode single -p config/LJSpeech/preprocess.yaml -m config/LJSpeech/model.yaml -t config/LJSpeech/train.yaml
 ```
 The generated utterances will be put in ``output/result/``.
 
@@ -37,7 +37,7 @@ The generated utterances will be put in ``output/result/``.
 Batch inference is also supported, try
 
 ```
-python3 synthesize.py --source preprocessed_data/LJSpeech/val.txt --restore_step 900000 --mode batch -p config/LJSpeech/preprocess.yaml -m config/LJSpeech/model.yaml -t config/LJSpeech/train.yaml
+python3 synthesize.py --source preprocessed_data/LJSpeech/val.txt --restore_step 160000 --mode batch -p config/LJSpeech/preprocess.yaml -m config/LJSpeech/model.yaml -t config/LJSpeech/train.yaml
 ```
 to synthesize all utterances in ``preprocessed_data/LJSpeech/val.txt``
 
@@ -46,7 +46,7 @@ The pitch/volume/speaking rate of the synthesized utterances can be controlled b
 For example, one can increase the speaking rate by 20 % and decrease the volume by 20 % by
 
 ```
-python3 synthesize.py --text "YOUR_DESIRED_TEXT" --restore_step 900000 --mode single -p config/LJSpeech/preprocess.yaml -m config/LJSpeech/model.yaml -t config/LJSpeech/train.yaml --duration_control 0.8 --energy_control 0.8
+python3 synthesize.py --text "YOUR_DESIRED_TEXT" --restore_step 160000 --mode single -p config/LJSpeech/preprocess.yaml -m config/LJSpeech/model.yaml -t config/LJSpeech/train.yaml --duration_control 0.8 --energy_control 0.8
 ```
 
 # Training
@@ -107,7 +107,9 @@ tensorboard --logdir output/log/LJSpeech
 to serve TensorBoard on your localhost.
 The loss curves, synthesized mel-spectrograms, and audios are shown.
 
-
+![](./img/tensorboard_loss.png)
+![](./img/tensorboard_spec.png)
+![](./img/tensorboard_audio.png)
 
 # Implementation Issues