Update README.md

README.md

@@ -18,7 +18,7 @@ metrics:
 
 This repository provides all the necessary tools to perform automatic speech
 recognition from an end-to-end system pretrained on CommonVoice (IT) within
-SpeechBrain. For a better experience we encourage you to learn more about
+SpeechBrain. For a better experience, we encourage you to learn more about
 [SpeechBrain](https://speechbrain.github.io). The given ASR model performance are:
 
 | Release | Test CER | Test WER | GPUs |
@@ -27,19 +27,19 @@ SpeechBrain. For a better experience we encourage you to learn more about
 
 ## Pipeline description
 
-This ASR system is composed with 2 different but linked blocks:
+This ASR system is composed of 2 different but linked blocks:
 1. Tokenizer (unigram) that transforms words into subword units and trained with
 the train transcriptions (train.tsv) of CommonVoice (IT).
-3. Acoustic model (CRDNN + CTC/Attention). The CRDNN architecture is made of
-N blocks of convolutional neural networks with normalisation and pooling on the
+2. Acoustic model (CRDNN + CTC/Attention). The CRDNN architecture is made of
+N blocks of convolutional neural networks with normalization and pooling on the
 frequency domain. Then, a bidirectional LSTM is connected to a final DNN to obtain
 the final acoustic representation that is given to the CTC and attention decoders.
 
 ## Intended uses & limitations
 
-This model has been primilarly developed to be run within SpeechBrain as a pretrained ASR model
+This model has been primarily developed to be run within SpeechBrain as a pretrained ASR model
 for the Italian language. Thanks to the flexibility of SpeechBrain, any of the 2 blocks
-detailed above can be extracted and connected to you custom pipeline as long as SpeechBrain is
+detailed above can be extracted and connected to your custom pipeline as long as SpeechBrain is
 installed.
 
 ## Install SpeechBrain