Update README.md

README.md

@@ -2,7 +2,7 @@ This repository provides a collection of widely popular text-to-speech (TTS) mod
 
 TTS is a two-step process - first you generate a MEL spectrogram using a TTS model and then you pass it to a VOCODER for generating the audio waveform.  We include both of these models inside this repository.  
 
-**Note** that these models are trained on [LJSpeech dataset](https://www.tensorflow.org/datasets/catalog/ljspeech).
+**Note** that these models are trained on [LJSpeech dataset](https://www.tensorflow.org/datasets/catalog/ljspeech) (except for the HiFi-GAN model).
 
 [Here’s a sample result](https://storage.googleapis.com/demo-experiments/demo_tts.wav) (with Fastspeech2 and MelGAN) for the text “Bill got in the habit of asking himself".
 
@@ -25,7 +25,7 @@ In the future, we may add more models.
 
 **Notes:**
 
-- Training data used for HiFi-GAN (MEL spectogram generation) is different w.r.t other models like Tacotron2, FastSpech2. So it is not compatible with the other architectures available in the repo.
+- Training data used for HiFi-GAN (MEL spectogram generation) is different w.r.t other models like Tacotron2, FastSpech2. So it is not compatible with the other architectures available inside this repo.
 - If you want to use HiFi-GAN in end-to-end scenario you can refer to this [notebook](https://github.com/jaywalnut310/glow-tts/blob/master/inference_hifigan.ipynb). In future we are planning to make it compatible with other architectures and add it in our [end-to-end notebook](https://github.com/tulasiram58827/TTS_TFLite/blob/main/End_to_End_TTS.ipynb). Stay tuned!
 
 ## About the Notebooks