#556The 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.
other,5-8-H01-1042,ak
newswire text . Some of the extracts were
<term>
expert human translations
</term>
, others were
<term>
machine translation
#702Some of the extracts wereexpert human translations, others were machine translation outputs.
other,12-2-H01-1042,ak
provide information about both the
<term>
human language learning process
</term>
, the
<term>
translation process
</term>
#593We 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,22-1-H01-1042,ak
devised for the
<term>
evaluation
</term>
of
<term>
human language learners
</term>
, to the
<term>
output
</term>
of
<term>
#566The 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,16-3-H01-1042,ak
the
<term>
intelligibility
</term>
of
<term>
MT output
</term>
. A
<term>
language learning experiment
#625This, the first experiment in a series of experiments, looks at the intelligibility ofMT output.
other,24-9-H01-1042,ak
expert human translation
</term>
or a
<term>
machine translation
</term>
. Additionally , they were asked
#736The subjects were given three minutes per extract to determine whether they believed the sample output to be an expert human translation or amachine translation.
other,18-4-H01-1042,ak
language essays
</term>
in less than 100
<term>
words
</term>
. Even more illuminating was the
#646A language learning experiment showed that assessors can differentiate native from non-native language essays in less than 100words.
other,16-6-H01-1042,ak
from duplicating the experiment using
<term>
machine translation output
</term>
. Subjects were given a set of up
#678We tested this to see if similar criteria could be elicited from duplicating the experiment usingmachine translation output.
other,11-8-H01-1042,ak
human translations
</term>
, others were
<term>
machine translation outputs
</term>
. The subjects were given three minutes
#708Some of the extracts were expert human translations, others weremachine translation outputs.
tech,24-2-H01-1042,ak
process
</term>
and the development of
<term>
machine translation systems
</term>
. This , the first experiment in
#605We believe that these evaluation techniques will provide information about both the human language learning process, the translation process and the development ofmachine translation systems.
tech,30-1-H01-1042,ak
</term>
, to the
<term>
output
</term>
of
<term>
machine translation ( MT ) systems
</term>
. We believe that these
<term>
evaluation
#574The 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,18-2-H01-1042,ak
language learning process
</term>
, the
<term>
translation process
</term>
and the development of
<term>
machine
#599We believe that these evaluation techniques will provide information about both the human language learning process, thetranslation process and the development of machine translation systems.
other,8-10-H01-1042,ak
Additionally , they were asked to mark the
<term>
word
</term>
at which they made this decision
#747Additionally, they were asked to mark theword at which they made this decision.
other,6-4-H01-1042,ak
learning experiment
</term>
showed that
<term>
assessors
</term>
can differentiate
<term>
native from
#634A language learning experiment showed thatassessors can differentiate native from non-native language essays in less than 100 words.
other,9-4-H01-1042,ak
<term>
assessors
</term>
can differentiate
<term>
native from non-native language essays
</term>
in less than 100
<term>
words
</term>
#637A language learning experiment showed that assessors can differentiatenative from non-native language essays in less than 100 words.
other,9-5-H01-1042,ak
illuminating was the factors on which the
<term>
assessors
</term>
made their decisions . We tested
#657Even more illuminating was the factors on which theassessors made their decisions.
tech,20-1-H01-1042,ak
</term>
, originally devised for the
<term>
evaluation
</term>
of
<term>
human language learners
</term>
#564The 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.
other,28-1-H01-1042,ak
human language learners
</term>
, to the
<term>
output
</term>
of
<term>
machine translation ( MT
#572The 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.
other,14-3-H01-1042,ak
series of experiments , looks at the
<term>
intelligibility
</term>
of
<term>
MT output
</term>
. A
<term>
#623This, the first experiment in a series of experiments, looks at theintelligibility of MT output.
other,19-9-H01-1042,ak
believed the sample output to be an
<term>
expert human translation
</term>
or a
<term>
machine translation
</term>
#731The subjects were given three minutes per extract to determine whether they believed the sample output to be anexpert human translation or a machine translation.