Merge pull request espnet#1963 from kan-bayashi/update_notebook_3

Update notebook

Author: mergify[bot]

README.md

@@ -282,13 +282,14 @@ You can download all of the pretrained models and generated samples:
 - [All of the pretrained E2E-TTS models](https://drive.google.com/open?id=1k9RRyc06Zl0mM2A7mi-hxNiNMFb_YzTF)
 - [All of the generated samples](https://drive.google.com/open?id=1bQGuqH92xuxOX__reWLP4-cif0cbpMLX)
 
-Note that in the generated samples we use three vocoders: Griffin-Lim (**GL**), WaveNet vocoder (**WaveNet**), Parallel WaveGAN (**ParallelWaveGAN**), and MelGAN (**MelGAN**).
+Note that in the generated samples we use the following vocoders: Griffin-Lim (**GL**), WaveNet vocoder (**WaveNet**), Parallel WaveGAN (**ParallelWaveGAN**), and MelGAN (**MelGAN**).
 The neural vocoders are based on following repositories.
-- [kan-bayashi/ParallelWaveGAN](https://github.com/kan-bayashi/ParallelWaveGAN): Parallel WaveGAN / MelGAN
+- [kan-bayashi/ParallelWaveGAN](https://github.com/kan-bayashi/ParallelWaveGAN): Parallel WaveGAN / MelGAN / Multi-band MelGAN
 - [r9y9/wavenet_vocoder](https://github.com/r9y9/wavenet_vocoder): 16 bit mixture of Logistics WaveNet vocoder
 - [kan-bayashi/PytorchWaveNetVocoder](https://github.com/kan-bayashi/PytorchWaveNetVocoder): 8 bit Softmax WaveNet Vocoder with the noise shaping
 
 If you want to build your own neural vocoder, please check the above repositories.
+[kan-bayashi/ParallelWaveGAN](https://github.com/kan-bayashi/ParallelWaveGAN) provides [the manual](https://github.com/kan-bayashi/ParallelWaveGAN#decoding-with-espnet-tts-models-features) about how to decode ESPnet-TTS model's features with neural vocoders. Please check it.
 
 Here we list all of the pretrained neural vocoders. Please download and enjoy the generation of high quality speech!