other,6-4-H01-1042,bq |
learning experiment
</term>
showed that
<term>
|
assessors
|
</term>
can differentiate
<term>
native from
|
#634
A language learning experiment showed thatassessors can differentiate native from non-native language essays in less than 100 words. |
other,9-5-H01-1042,bq |
illuminating was the factors on which the
<term>
|
assessors
|
</term>
made their decisions . We tested
|
#657
Even more illuminating was the factors on which theassessors made their decisions. |
tech,12-1-H01-1042,bq |
is to test the efficacy of applying
<term>
|
automated evaluation techniques
|
</term>
, originally devised for the
<term>
|
#556
The purpose of this research is to test the efficacy of applyingautomated evaluation techniques, originally devised for the evaluation of human language learners, to the output of machine translation (MT) systems. |
tech,22-2-H01-1042,bq |
<term>
translation process
</term>
and the
<term>
|
development
|
</term>
of
<term>
machine translation systems
|
#603
We believe that these evaluation techniques will provide information about both the human language learning process, the translation process and thedevelopment of machine translation systems. |
tech,20-1-H01-1042,bq |
</term>
, originally devised for the
<term>
|
evaluation
|
</term>
of
<term>
human language learners
</term>
|
#564
The purpose of this research is to test the efficacy of applying automated evaluation techniques, originally devised for theevaluation of human language learners, to the output of machine translation (MT) systems. |
tech,4-2-H01-1042,bq |
systems
</term>
. We believe that these
<term>
|
evaluation techniques
|
</term>
will provide information about both
|
#585
We believe that theseevaluation techniques will provide information about both the human language learning process, the translation process and the development of machine translation systems. |
other,19-9-H01-1042,bq |
believed the sample output to be an
<term>
|
expert human translation
|
</term>
or a
<term>
machine translation
</term>
|
#731
The subjects were given three minutes per extract to determine whether they believed the sample output to be anexpert human translation or a machine translation. |
other,5-8-H01-1042,bq |
</term>
. Some of the extracts were
<term>
|
expert human translations
|
</term>
, others were
<term>
machine translation
|
#702
Some of the extracts wereexpert human translations, others were machine translation outputs. |
other,22-1-H01-1042,bq |
devised for the
<term>
evaluation
</term>
of
<term>
|
human language learners
|
</term>
, to the
<term>
output
</term>
of
<term>
|
#566
The purpose of this research is to test the efficacy of applying automated evaluation techniques, originally devised for the evaluation ofhuman language learners, to the output of machine translation (MT) systems. |
other,12-2-H01-1042,bq |
provide information about both the
<term>
|
human language learning process
|
</term>
, the
<term>
translation process
</term>
|
#593
We believe that these evaluation techniques will provide information about both thehuman language learning process, the translation process and the development of machine translation systems. |
other,14-3-H01-1042,bq |
series of experiments , looks at the
<term>
|
intelligibility
|
</term>
of
<term>
MT output
</term>
. A
<term>
|
#623
This, the first experiment in a series of experiments, looks at theintelligibility of MT output. |
other,1-4-H01-1042,bq |
</term>
of
<term>
MT output
</term>
. A
<term>
|
language learning experiment
|
</term>
showed that
<term>
assessors
</term>
|
#629
Alanguage learning experiment showed that assessors can differentiate native from non-native language essays in less than 100 words. |
other,24-9-H01-1042,bq |
expert human translation
</term>
or a
<term>
|
machine translation
|
</term>
. Additionally , they were asked
|
#736
The subjects were given three minutes per extract to determine whether they believed the sample output to be an expert human translation or amachine translation. |
tech,30-1-H01-1042,bq |
</term>
, to the
<term>
output
</term>
of
<term>
|
machine translation ( MT ) systems
|
</term>
. We believe that these
<term>
evaluation
|
#574
The purpose of this research is to test the efficacy of applying automated evaluation techniques, originally devised for the evaluation of human language learners, to the output ofmachine translation ( MT ) systems. |
other,16-6-H01-1042,bq |
from duplicating the experiment using
<term>
|
machine translation output
|
</term>
. Subjects were given a set of up
|
#678
We tested this to see if similar criteria could be elicited from duplicating the experiment usingmachine translation output. |
other,11-8-H01-1042,bq |
human translations
</term>
, others were
<term>
|
machine translation outputs
|
</term>
. The subjects were given three minutes
|
#708
Some of the extracts were expert human translations, others weremachine translation outputs. |
tech,24-2-H01-1042,bq |
</term>
and the
<term>
development
</term>
of
<term>
|
machine translation systems
|
</term>
. This , the first experiment in
|
#605
We believe that these evaluation techniques will provide information about both the human language learning process, the translation process and the development ofmachine translation systems. |
other,16-3-H01-1042,bq |
the
<term>
intelligibility
</term>
of
<term>
|
MT output
|
</term>
. A
<term>
language learning experiment
|
#625
This, the first experiment in a series of experiments, looks at the intelligibility ofMT output. |
other,9-4-H01-1042,bq |
<term>
assessors
</term>
can differentiate
<term>
|
native from non-native language essays
|
</term>
in less than 100
<term>
words
</term>
|
#637
A language learning experiment showed that assessors can differentiatenative from non-native language essays in less than 100 words. |
other,28-1-H01-1042,bq |
human language learners
</term>
, to the
<term>
|
output
|
</term>
of
<term>
machine translation ( MT
|
#572
The purpose of this research is to test the efficacy of applying automated evaluation techniques, originally devised for the evaluation of human language learners, to theoutput of machine translation (MT) systems. |