Dialog State Tracking: A Neural Reading Comprehension Approach

Dialog Comments

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A sub-dialog \(D_t\) of a dialog D is defined by the values of the constituent slots \(S_t\) and hence Dt is defined as \(D_t = {s_1(t), s_2(t),....,s_M(t)}\).



  1. Slot Carryover Model - A model to decide if we’ve to carry over the slot value from previous turn or not. This is equal to \(sigmoid(e(t). W_i)\) . Wi is for all slots - the carry over model for all slots is predicted together.
  2. Slot Type Model - For every slot, predict if it belongs to {Yes, No, DontCare, Span}. We concatenate the dialog representation with the question embedding and pass it through a feed forward layer followed by a softmax.
  3. Slot Span Model - The question vector qi acts as the question and the dialog encoding \({d_1, d_2, d_L}\) acts as the context. Pick a span within the context that has the slot.


  1. For slot carry over models, we do a joint prediction and get M binary vector (whether to carry over the value for all slots).
  2. For slot type and slot span models, we treat dialog question pairs (Dt, qi) as separate prediction tasks for each slot.


Paper Accuracy on MultiWoz 2.0
This paper 39.21
HyST (ensemble) 44.22
This paper + JST 47.33

Kaushik Rangadurai

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