Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Dialogue Strategy Adaptation to New Action Sets Using Multi-dimensional
  Modelling   A major bottleneck for building statistical spoken dialogue systems for new
domains and applications is the need for large amounts of training data. To
address this problem, we adopt the multi-dimensional approach to dialogue
management and evaluate its potential for transfer learning. Specifically, we
exploit pre-trained task-independent policies to speed up training for an
extended task-specific action set, in which the single summary action for
requesting a slot is replaced by multiple slot-specific request actions. Policy
optimisation and evaluation experiments using an agenda-based user simulator
show that with limited training data, much better performance levels can be
achieved when using the proposed multi-dimensional adaptation method. We
confirm this improvement in a crowd-sourced human user evaluation of our spoken
dialogue system, comparing partially trained policies. The multi-dimensional
system (with adaptation on limited training data in the target scenario)
outperforms the one-dimensional baseline (without adaptation on the same amount
of training data) by 7% perceived success rate.

7
The categories of this paper are: hep-th
31
The categories of this paper are: ao-sci
21
The categories of this paper are: adap-org
24
The categories of this paper are: dg-ga
3
The categories of this paper are: physics
29
The categories of this paper are: funct-an
30
The categories of this paper are: q-alg
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The categories of this paper are: mtrl-th
8
The categories of this paper are: hep-ex
28
The categories of this paper are: alg-geom
17
The categories of this paper are: q-fin
13
The categories of this paper are: quant-ph
5
The categories of this paper are: gr-qc
27
The categories of this paper are: comp-gas
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The categories of this paper are: solv-int
4
The categories of this paper are: cond-mat