| P06-1119 | ontologies by simply applying | off-the-shelf machine translation | . General-purpose translation |
| S13-2021 | three steps . Firstly , we use a | off-the-shelf machine translation | ( MT ) tool to convert the two |
| D10-1103 | major drawbacks . First , most | off-the-shelf machine translation | systems typically generate only |
| D10-1103 | translation of the text as most | off-the-shelf machine translation | tools do . EM ( Model Translation |
| E14-1072 | ESL sentence with outputs from | off-the-shelf machine translation | systems . We propose a redundancy |
| C02-1070 | domain , we employ commer - cial , | off-the-shelf machine translation | to generate an artificial parallel |
| P14-1055 | Projection via MT Among the several | off-the-shelf machine translation | services , we select the Google |
| W97-0901 | what was in the text . Output of | off-the-shelf machine translation | ( MT ) systems are often of low |
| A97-1049 | what is in the text . Outputs of | off-the-shelf machine translation | ( MT ) systems are often of low-quality |
