Update app.py

app.py

@@ -45,12 +45,12 @@ outputs =  gr.outputs.Audio(type="file", label="Output Audio")
 
 
 title = "Tensorflow TTS"
-description = "demo for VITS: Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech. To use it, simply add your text, or click one of the examples to load them. Read more at the links below."
-article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2106.06103'>Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech</a> | <a href='https://github.com/jaywalnut310/vits'>Github Repo</a></p>"
+description = "demo for TensorFlowTTS: Real-Time State-of-the-art Speech Synthesis for Tensorflow 2. To use it, simply add your text, or click one of the examples to load them. Read more at the links below."
+article = "<p style='text-align: center'><a href='https://tensorspeech.github.io/TensorFlowTTS/'>TensorFlowTTS: Real-Time State-of-the-art Speech Synthesis for Tensorflow 2 (supported including English, French, Korean, Chinese, German and Easy to adapt for other languages)</a> | <a href='https://github.com/TensorSpeech/TensorFlowTTS'>Github Repo</a></p>"
 
 examples = [
- ["We propose VITS, Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech."],
- ["Our method adopts variational inference augmented with normalizing flows and an adversarial training process, which improves the expressive power of generative modeling."]   
+ ["TensorFlowTTS provides real-time state-of-the-art speech synthesis architectures such as Tacotron-2, Melgan, Multiband-Melgan, FastSpeech, FastSpeech2 based-on TensorFlow 2."],
+ ["With Tensorflow 2, we can speed-up training/inference progress, optimizer further by using fake-quantize aware and pruning, make TTS models can be run faster than real-time and be able to deploy on mobile devices or embedded systems."]   
 ]
 
 gr.Interface(inference, inputs, outputs, title=title, description=description, article=article, examples=examples).launch()