Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: End-to-End Joint Learning of Natural Language Understanding and Dialogue
  Manager   Natural language understanding and dialogue policy learning are both
essential in conversational systems that predict the next system actions in
response to a current user utterance. Conventional approaches aggregate
separate models of natural language understanding (NLU) and system action
prediction (SAP) as a pipeline that is sensitive to noisy outputs of
error-prone NLU. To address the issues, we propose an end-to-end deep recurrent
neural network with limited contextual dialogue memory by jointly training NLU
and SAP on DSTC4 multi-domain human-human dialogues. Experiments show that our
proposed model significantly outperforms the state-of-the-art pipeline models
for both NLU and SAP, which indicates that our joint model is capable of
mitigating the affects of noisy NLU outputs, and NLU model can be refined by
error flows backpropagating from the extra supervised signals of system
actions.

22
The categories of this paper are: chao-dyn
7
The categories of this paper are: hep-th
18
The categories of this paper are: econ
17
The categories of this paper are: q-fin
32
The categories of this paper are: atom-ph
28
The categories of this paper are: alg-geom
12
The categories of this paper are: nucl-th
15
The categories of this paper are: nucl-ex
19
The categories of this paper are: eess
11
The categories of this paper are: hep-lat
23
The categories of this paper are: solv-int
24
The categories of this paper are: dg-ga
35
The categories of this paper are: mtrl-th
10
The categories of this paper are: q-bio
4
The categories of this paper are: cond-mat
33
The categories of this paper are: plasm-ph