👌 Update README.

Author: dathudeptrai

README.md

@@ -19,6 +19,7 @@
 :zany_face: 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](https://www.tensorflow.org/model_optimization/guide/quantization/training_comprehensive_guide) and [pruning](https://www.tensorflow.org/model_optimization/guide/pruning/pruning_with_keras), make TTS models can be run faster than real-time and be able to deploy on mobile devices or embedded systems.
 
 ## What's new
+- 2020/11/24 **(NEW!)** Add HiFi-GAN vocoder. See [here](https://github.com/TensorSpeech/TensorFlowTTS/tree/master/examples/hifigan)
 - 2020/11/19 **(NEW!)** Add Multi-GPU gradient accumulator. See [here](https://github.com/TensorSpeech/TensorFlowTTS/pull/377)
 - 2020/08/23  Add Parallel WaveGAN tensorflow implementation. See [here](https://github.com/TensorSpeech/TensorFlowTTS/tree/master/examples/parallel_wavegan)
 - 2020/08/23 Add MBMelGAN G + ParallelWaveGAN G example. See [here](https://github.com/TensorSpeech/TensorFlowTTS/tree/master/examples/multiband_pwgan)
@@ -85,6 +86,7 @@ TensorFlowTTS currently  provides the following architectures:
 4. **Multi-band MelGAN** released with the paper [Multi-band MelGAN: Faster Waveform Generation for High-Quality Text-to-Speech](https://arxiv.org/abs/2005.05106) by Geng Yang, Shan Yang, Kai Liu, Peng Fang, Wei Chen, Lei Xie.
 5. **FastSpeech2** released with the paper [FastSpeech 2: Fast and High-Quality End-to-End Text to Speech](https://arxiv.org/abs/2006.04558) by Yi Ren, Chenxu Hu, Xu Tan, Tao Qin, Sheng Zhao, Zhou Zhao, Tie-Yan Liu.
 6. **Parallel WaveGAN** released with the paper [Parallel WaveGAN: A fast waveform generation model based on generative adversarial networks with multi-resolution spectrogram](https://arxiv.org/abs/1910.11480) by Ryuichi Yamamoto, Eunwoo Song, Jae-Min Kim.
+7. **HiFi-GAN** released with the paper [HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis](https://arxiv.org/abs/2010.05646) by Jungil Kong, Jaehyeon Kim, Jaekyoung Bae.
 
 We are also implementing some techniques to improve quality and convergence speed from the following papers:
 
@@ -217,6 +219,7 @@ To know how to train model from scratch or fine-tune with other datasets/languag
 - For Multiband-MelGAN tutorial, pls see [examples/multiband_melgan](https://github.com/tensorspeech/TensorFlowTTS/tree/master/examples/multiband_melgan)
 - For Parallel WaveGAN tutorial, pls see [examples/parallel_wavegan](https://github.com/tensorspeech/TensorFlowTTS/tree/master/examples/parallel_wavegan)
 - For Multiband-MelGAN Generator + Parallel WaveGAN Discriminator tutorial, pls see [examples/multiband_pwgan](https://github.com/tensorspeech/TensorFlowTTS/tree/master/examples/multiband_pwgan)
+- For HiFi-GAN tutorial, pls see [examples/hifigan](https://github.com/tensorspeech/TensorFlowTTS/tree/master/examples/hifigan)
 # Abstract Class Explaination
 
 ## Abstract DataLoader Tensorflow-based dataset