# 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. To illustrate the model implementation in detail, 5 parts is introduced.  
     1. Feature Extraction.
     2. 2D Convolution subsampling layer.
     3. RNN layer with only forward direction.
     4. Softmax Layer.
     5. CTC Decoder.


 # 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}