English-Latvian SMT: knowledge or data?

In cases when phrase-based statistical machine translation (SMT) is applied to languages with rather free word order and rich morphology, translated texts often are not fluent due to misused inflectional forms and wrong word order between phrases or even inside the phrase. One of possible solutions how to improve translation quality is to apply factored models. The paper presents work on English-Latvian phrase-based and factored SMT systems and, using evaluation results, demonstrates that although factored models seem more appropriate for highly inflected languages, they have rather small influence on translation results, while using phrase-model with more data better translation quality could be achieved.