Using Discourse Structure Improves Machine Translation Evaluation
Code (0)
등록된 구현이 없습니다.
Tasks
Machine TranslationTranslationSimilar Papers 제목 키워드 기반
Discourse Structure in Machine Translation Evaluation
In this article, we explore the potential of using sentence-level discourse structure for machine translation evaluation. We first design discourse-aware similarity measures, which use all-subtree kernels to compare disc…
Machine TranslationSentenceTranslationDiscoTK: Using Discourse Structure for Machine Translation Evaluation
We present novel automatic metrics for machine translation evaluation that use discourse structure and convolution kernels to compare the discourse tree of an automatic translation with that of the human reference. We ex…
Machine TranslationTranslationOn Integrating Discourse in Machine Translation
As the quality of Machine Translation (MT) improves, research on improving discourse in automatic translations becomes more viable. This has resulted in an increase in the amount of work on discourse in MT. However many …
Machine TranslationTranslationA Bilingual Discourse Corpus and Its Applications
Existing discourse research only focuses on the monolingual languages and the inconsistency between languages limits the power of the discourse theory in multilingual applications such as machine translation. To address …
Machine TranslationTranslationDiscourse Centric Evaluation of Machine Translation with a Densely Annotated Parallel Corpus
Several recent papers claim human parity at sentence-level Machine Translation (MT), especially in high-resource languages. Thus, in response, the MT community has, in part, shifted its focus to document-level translatio…
Machine TranslationSentenceTranslation