| measure(ment),5-1-N03-2006,ak | N-grams </term> . In order to boost the <term> | translation quality | </term> of <term> EBMT </term> based on a <term> | #3085 In order to boost thetranslation quality of EBMT based on a small-sized bilingual corpus, we use an out-of-domain bilingual corpus and, in addition, the language model of an in-domain monolingual corpus. | |
| tech,8-1-N03-2006,ak | <term> translation quality </term> of <term> | EBMT | </term> based on a <term> small-sized bilingual | #3088 In order to boost the translation quality ofEBMT based on a small-sized bilingual corpus, we use an out-of-domain bilingual corpus and, in addition, the language model of an in-domain monolingual corpus. | |
| lr,12-1-N03-2006,ak | </term> of <term> EBMT </term> based on a <term> | small-sized bilingual corpus | </term> , we use an <term> out-of-domain bilingual | #3092 In order to boost the translation quality of EBMT based on asmall-sized bilingual corpus, we use an out-of-domain bilingual corpus and, in addition, the language model of an in-domain monolingual corpus. | |
| lr,19-1-N03-2006,ak | bilingual corpus </term> , we use an <term> | out-of-domain bilingual corpus | </term> and , in addition , the <term> language | #3099 In order to boost the translation quality of EBMT based on a small-sized bilingual corpus, we use anout-of-domain bilingual corpus and, in addition, the language model of an in-domain monolingual corpus. | |
| model,28-1-N03-2006,ak | corpus </term> and , in addition , the <term> | language model | </term> of an <term> in-domain monolingual | #3108 In order to boost the translation quality of EBMT based on a small-sized bilingual corpus, we use an out-of-domain bilingual corpus and, in addition, thelanguage model of an in-domain monolingual corpus. | |
| lr,32-1-N03-2006,ak | the <term> language model </term> of an <term> | in-domain monolingual corpus | </term> . We conducted experiments with an | #3112 In order to boost the translation quality of EBMT based on a small-sized bilingual corpus, we use an out-of-domain bilingual corpus and, in addition, the language model of anin-domain monolingual corpus. | |
| tech,5-2-N03-2006,ak | . We conducted experiments with an <term> | EBMT system | </term> . The two <term> evaluation measures | #3121 We conducted experiments with anEBMT system. | |
| measure(ment),2-3-N03-2006,ak | an <term> EBMT system </term> . The two <term> | evaluation measures | </term> of the <term> BLEU score </term> and | #3126 The twoevaluation measures of the BLEU score and the NIST score demonstrated the effect of using an out-of-domain bilingual corpus and the possibility of using the language model. | |
| measure(ment),6-3-N03-2006,ak | <term> evaluation measures </term> of the <term> | BLEU score | </term> and the <term> NIST score </term> demonstrated | #3130 The two evaluation measures of theBLEU score and the NIST score demonstrated the effect of using an out-of-domain bilingual corpus and the possibility of using the language model. | |
| measure(ment),10-3-N03-2006,ak | the <term> BLEU score </term> and the <term> | NIST score | </term> demonstrated the effect of using | #3134 The two evaluation measures of the BLEU score and theNIST score demonstrated the effect of using an out-of-domain bilingual corpus and the possibility of using the language model. | |
| lr,18-3-N03-2006,ak | demonstrated the effect of using an <term> | out-of-domain bilingual corpus | </term> and the possibility of using the <term> | #3142 The two evaluation measures of the BLEU score and the NIST score demonstrated the effect of using anout-of-domain bilingual corpus and the possibility of using the language model. | |
| model,27-3-N03-2006,ak | </term> and the possibility of using the <term> | language model | </term> . We describe a simple <term> unsupervised | #3151 The two evaluation measures of the BLEU score and the NIST score demonstrated the effect of using an out-of-domain bilingual corpus and the possibility of using thelanguage model. |
