title: How to feed variable-length of speech feature to RNN(LSTM) for Speech Recognition?
body: <p>I am trying to build a Speech Recognition System, which is a squence-to-sequence model. But I got confused about how to feed the extracted feature(fbank with the dimension of 40) to LSTM. As far as I have found, there are different methods to feed the data as input into LSTM. However, I have a doubt to fully understand them. I would be so thankful if someone tells me whether or not I am correct in the following cases.</p>
  
  <p><strong>Case 1:</strong>
  In the convenient format [<em>Batch_Size</em>, <em>Time_Step</em>, <em>Feature_Dim</em>], If I select [1, <em>None</em>, 40], the length of each sequence(utterance) can be varied? if so, in this case I do not need to pad each sequence, am I right?</p>
  
  <p><strong>Case 2:</strong> 
  If all input sequences are padded to the same length, the Batch_Size can be any value like 64, 128 and etc?</p>
  
  <p>Finally, one more question, do I notice that the Time_Step in each Batch should be the same?</p>
  
  <p>I would be so thankful if someone can help me to get rid of my doubts or give me some suggestions. </p>