From 1b680a9690c1a9d174294b222a6b3b9a5dacea43 Mon Sep 17 00:00:00 2001
From: Derry Tutt <82726593+everypizza1@users.noreply.github.com>
Date: Tue, 26 Dec 2023 07:52:02 -0600
Subject: [PATCH] Update README.en.md

Made it seem more human.
---
 docs/en/README.en.md | 25 ++++++++++++-------------
 1 file changed, 12 insertions(+), 13 deletions(-)

diff --git a/docs/en/README.en.md b/docs/en/README.en.md
index 7e1889d..9c17df3 100644
--- a/docs/en/README.en.md
+++ b/docs/en/README.en.md
@@ -32,26 +32,25 @@ Realtime Voice Conversion GUI：go-realtime-gui.bat
 
 ![image](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/assets/129054828/143246a9-8b42-4dd1-a197-430ede4d15d7)
 
-> The dataset for the pre-training model uses nearly 50 hours of high quality VCTK open source dataset.
+> The dataset for the pre-training model uses nearly 50 hours of high quality audio from the VCTK open source dataset.
 
-> High quality licensed song datasets will be added to training-set one after another for your use, without worrying about copyright infringement.
+> High quality licensed song datasets will be added to the training-set often for your use, without having to worry about copyright infringement.
 
 > Please look forward to the pretrained base model of RVCv3, which has larger parameters, more training data, better results, unchanged inference speed, and requires less training data for training.
 
-## Summary
-This repository has the following features:
+## Features:
 + Reduce tone leakage by replacing the source feature to training-set feature using top1 retrieval;
-+ Easy and fast training, even on relatively poor graphics cards;
-+ Training with a small amount of data also obtains relatively good results (>=10min low noise speech recommended);
-+ Supporting model fusion to change timbres (using ckpt processing tab->ckpt merge);
-+ Easy-to-use Webui interface;
-+ Use the UVR5 model to quickly separate vocals and instruments.
-+ Use the most powerful High-pitch Voice Extraction Algorithm [InterSpeech2023-RMVPE](#Credits) to prevent the muted sound problem. Provides the best results (significantly) and is faster, with even lower resource consumption than Crepe_full.
-+ AMD/Intel graphics cards acceleration supported.
++ Easy + fast training, even on poor graphics cards;
++ Training with a small amounts of data (>=10min low noise speech recommended);
++ Model fusion to change timbres (using ckpt processing tab->ckpt merge);
++ Easy-to-use WebUI;
++ UVR5 model to quickly separate vocals and instruments;
++ High-pitch Voice Extraction Algorithm [InterSpeech2023-RMVPE](#Credits) to prevent a muted sound problem. Provides the best results (significantly) and is faster with lower resource consumption than Crepe_full;
++ AMD/Intel graphics cards acceleration supported;
 + Intel ARC graphics cards acceleration with IPEX supported.
 
 ## Preparing the environment
-The following commands need to be executed in the environment of Python version 3.8 or higher.
+The following commands need to be executed with Python 3.8 or higher.
 
 (Windows/Linux)
 First install the main dependencies through pip:
@@ -166,7 +165,7 @@ You might also need to set these environment variables (e.g. on a RX6700XT):
 export ROCM_PATH=/opt/rocm
 export HSA_OVERRIDE_GFX_VERSION=10.3.0
 ````
-Also make sure your user is part of the `render` and `video` group:
+Make sure your user is part of the `render` and `video` group:
 ````
 sudo usermod -aG render $USERNAME
 sudo usermod -aG video $USERNAME