Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Domain Adaptation with Clustered Language Models   In this paper, a method of domain adaptation for clustered language models is
developed. It is based on a previously developed clustering algorithm, but with
a modified optimisation criterion. The results are shown to be slightly
superior to the previously published 'Fillup' method, which can be used to
adapt standard n-gram models. However, the improvement both methods give
compared to models built from scratch on the adaptation data is quite small
(less than 11% relative improvement in word error rate). This suggests that
both methods are still unsatisfactory from a practical point of view.

17
The categories of this paper are: q-fin
8
The categories of this paper are: hep-ex
32
The categories of this paper are: atom-ph
10
The categories of this paper are: q-bio
34
The categories of this paper are: chem-ph
16
The categories of this paper are: stat
4
The categories of this paper are: cond-mat
37
The categories of this paper are: supr-con
7
The categories of this paper are: hep-th
29
The categories of this paper are: funct-an
21
The categories of this paper are: adap-org
31
The categories of this paper are: ao-sci
2
The categories of this paper are: math
19
The categories of this paper are: eess
0
The categories of this paper are: hep-ph
23
The categories of this paper are: solv-int