Кросс-лингвистикалық тәуелділік талдау

This paper proposes to learn language- independent word representations to ad- dress cross-lingual dependency parsing, which aims to predict the dependency parsing trees for sentences in the target language by …...

Cross-lingual dependency parsing aims to train a dependency parser for an annotation-scarce target language by ex- ploiting annotated training data from an annotation-rich source language, which is of great importance …...

AbstractSinglish can be interesting to the ACL community both linguistically as a major creole based on English, and computationally for information extraction and sentiment analysis of regional social media. We …...

AbstractCross-lingual transfer learning has become an important weapon to battle the unavailability of annotated resources for low-resource languages. One of the fundamental techniques to transfer across languages is learning language-agnostic …...

AbstractThe best solution of structured prediction models in NLP is often inaccurate because of limited expressive power of the model or to non-exact parameter estimation. One way to mitigate this …...

AbstractWe propose a novel approach to cross-lingual dependency parsing based on word reordering. The words in each sentence of a source language corpus are rearranged to meet the word order …...

AbstractCross-lingual language tasks typically require a substantial amount of annotated data or parallel translation data. We explore whether language representations that capture relationships among languages can be learned and subsequently …...

AbstractMeta-learning, or learning to learn, is a technique that can help to overcome resource scarcity in cross-lingual NLP problems, by enabling fast adaptation to new tasks. We apply model-agnostic meta-learning …...