Update modle_arcitecture.md

doc/src/modle_arcitecture.md

@@ -1,17 +1,25 @@
 # Model Arcitecture
 
  The implemented arcitecure of Deepspeech2 online model is based on [Deepspeech2 model](https://arxiv.org/pdf/1512.02595.pdf) with some changes. 
- The figure of arcitecture is shown in ![image](../image/ds2onlineModel.png).
+ The model is mainly composed of 2D convolution subsampling layer and single direction rnn layers. 
- The model is mainly composed of 2D convolution subsampling layer and single direction rnn layers. To illustrate the model implementation in detail, 5 parts is introduced.  
+ To illustrate the model implementation clearly, 5 parts is described in detail.  
      1. Feature Extraction.
      2. 2D Convolution subsampling layer.
      3. RNN layer with only forward direction.
      4. Softmax Layer.
      5. CTC Decoder.
+The arcitecture of the model is shown in Fig.1. 
 
+<p align="center">
+<img src="../images/ds2onlineModel.png" width=800> 
+<br/>Fig.1 The Arcitecture of deepspeech2 online modle
+</p>
 
- # Feature Extraction
+# Feature Extraction
 
  Three methods of feature extraction is implemented, which are linear, fbank and mfcc.
  For a single utterance $x^i$ sampled from the training set $S$,
  $ S= {(x^1,y^1),(x^2,y^2),...,(x^m,y^m)}$, where $y^i$ is the label correspodding to the ${x^i}
+
+# Backbone
+The Backbone is composed of 2D Convolution subsampling layer.