LAMB: A Good Shepherd of Morphologically Rich Languages
Code (0)
등록된 구현이 없습니다.
Tasks
LemmatizationSimilar Papers 제목 키워드 기반
Cross-Lingual Word Embeddings for Morphologically Rich Languages
Cross-lingual word embedding models learn a shared vector space for two or more languages so that words with similar meaning are represented by similar vectors regardless of their language. Although the existing models a…
Cross-Lingual Word EmbeddingsTranslationWord EmbeddingsWord TranslationCSSL: Contrastive Self-Supervised Learning for Dependency Parsing on Relatively Free Word Ordered and Morphologically Rich Low Resource Languages
Neural dependency parsing has achieved remarkable performance for low resource morphologically rich languages. It has also been well-studied that morphologically rich languages exhibit relatively free word order. This pr…
Data AugmentationDependency ParsingSelf-Supervised LearningWord Representation Models for Morphologically Rich Languages in Neural Machine Translation
Dealing with the complex word forms in morphologically rich languages is an open problem in language processing, and is particularly important in translation. In contrast to most modern neural systems of translation, whi…
Hard AttentionMachine TranslationTranslationWord Semantic Similarity for Morphologically Rich Languages
In this work, we investigate the role of morphology on the performance of semantic similarity for morphologically rich languages, such as German and Greek. The challenge in processing languages with richer morphology tha…
Semantic SimilaritySemantic Textual SimilarityNeural disambiguation of lemma and part of speech in morphologically rich languages
We consider the problem of disambiguating the lemma and part of speech of ambiguous words in morphologically rich languages. We propose a method for disambiguating ambiguous words in context, using a large un-annotated c…
LEMMAPOS