tech,0-1-C04-1103,bq |
<term>
referring expressions
</term>
.
<term>
|
Machine
transliteration/back-transliteration
|
</term>
plays an important role in many
<term>
|
#5729
The evaluation using another 23 subjects showed that the proposed method could effectively generate proper referring expressions. Machine transliteration/back-transliteration plays an important role in many multilingual speech and language applications. |
other,8-1-C04-1103,bq |
</term>
plays an important role in many
<term>
|
multilingual
speech and language applications
|
</term>
. In this paper , a novel framework
|
#5737
Machine transliteration/back-transliteration plays an important role in many multilingual speech and language applications. |
tech,8-2-C04-1103,bq |
this paper , a novel framework for
<term>
|
machine
transliteration/back transliteration
|
</term>
that allows us to carry out
<term>
|
#5751
In this paper, a novel framework for machine transliteration/back transliteration that allows us to carry out direct orthographical mapping (DOM) between two different languages is presented. |
other,17-2-C04-1103,bq |
</term>
that allows us to carry out
<term>
|
direct
orthographical mapping ( DOM )
|
</term>
between two different
<term>
languages
|
#5760
In this paper, a novel framework for machine transliteration/back transliteration that allows us to carry out direct orthographical mapping ( DOM ) between two different languages is presented. |
other,26-2-C04-1103,bq |
DOM )
</term>
between two different
<term>
|
languages
|
</term>
is presented . Under this framework
|
#5769
In this paper, a novel framework for machine transliteration/back transliteration that allows us to carry out direct orthographical mapping (DOM) between two different languages is presented. |
model,5-3-C04-1103,bq |
presented . Under this framework , a
<term>
|
joint
source-channel transliteration model
|
</term>
, also called
<term>
n-gram transliteration
|
#5778
Under this framework, a joint source-channel transliteration model, also called n-gram transliteration model (ngram TM), is further proposed to model the transliteration process. |
model,12-3-C04-1103,bq |
transliteration model
</term>
, also called
<term>
|
n-gram
transliteration model ( ngram TM )
|
</term>
, is further proposed to model the
|
#5785
Under this framework, a joint source-channel transliteration model, also called n-gram transliteration model ( ngram TM ), is further proposed to model the transliteration process. |
tech,26-3-C04-1103,bq |
is further proposed to model the
<term>
|
transliteration
process
|
</term>
. We evaluate the proposed methods
|
#5799
Under this framework, a joint source-channel transliteration model, also called n-gram transliteration model (ngram TM), is further proposed to model the transliteration process. |
tech,7-4-C04-1103,bq |
proposed methods through several
<term>
|
transliteration/back
transliteration
|
</term>
experiments for
<term>
English/Chinese
|
#5809
We evaluate the proposed methods through several transliteration/back transliteration experiments for English/Chinese and English/Japanese language pairs. |
other,11-4-C04-1103,bq |
transliteration
</term>
experiments for
<term>
|
English/Chinese
and English/Japanese language pairs
|
</term>
. Our study reveals that the proposed
|
#5813
We evaluate the proposed methods through several transliteration/back transliteration experiments for English/Chinese and English/Japanese language pairs. |
measure(ment),19-5-C04-1103,bq |
development effort but also improves the
<term>
|
transliteration
accuracy
|
</term>
significantly . The reality of
<term>
|
#5838
Our study reveals that the proposed method not only reduces an extensive system development effort but also improves the transliteration accuracy significantly. |