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Lab 4, SDS 2016

Content

Homework - RNN DST

  • Report bugs
  • Come up with a RNN model encoded as Tensorflow computation graph
    • Implement it in tracker/GRUmodel.py
    • Use RNN for encode inputs from each turn sys_utt + DELIM + user_utt
    • For each turn predict the slots based on the last state from the RNN
      • This model does in fact more SLU (spoken language understanding) because it does care about history
      • If you have this model working start refactoring the code for using encoding dialogue history with another RNN