Combining Word Reordering Methods on different Linguistic Abstraction Levels for Statistical Machine Translation
Code (0)
등록된 구현이 없습니다.
Tasks
Machine TranslationTranslationSimilar Papers 제목 키워드 기반
A Survey of Word Reordering in Statistical Machine Translation: Computational Models and Language Phenomena
Word reordering is one of the most difficult aspects of statistical machine translation (SMT), and an important factor of its quality and efficiency. Despite the vast amount of research published to date, the interest of…
Machine TranslationTranslationUniversal Reordering via Linguistic Typology
In this paper we explore the novel idea of building a single universal reordering model from English to a large number of target languages. To build this model we exploit typological features of word order for a large nu…
DecoderMachine TranslationTranslationAn empirical analysis of phrase-based and neural machine translation
Two popular types of machine translation (MT) are phrase-based and neural machine translation systems. Both of these types of systems are composed of multiple complex models or layers. Each of these models and layers lea…
Machine TranslationTranslationWord Alignment-Based Reordering of Source Chunks in PB-SMT
Reordering poses a big challenge in statistical machine translation between distant language pairs. The paper presents how reordering between distant language pairs can be handled efficiently in phrase-based statistical …
Machine TranslationTranslationWord AlignmentImplicit Word Reordering with Knowledge Distillation for Cross-Lingual Dependency Parsing
Word order difference between source and target languages is a major obstacle to cross-lingual transfer, especially in the dependency parsing task. Current works are mostly based on order-agnostic models or word reorderi…
Cross-Lingual TransferDependency ParsingKnowledge DistillationSentence