paper-with-me

홈 › Papers

Same Referent, Different Words: Unsupervised Mining of Opaque Coreferent Mentions

2013-06-01 · NAACL 2013 6 · Marta Recasens, Matthew Can, Daniel Jurafsky
📄 PDF Abstract BibTeX

Code (0)

등록된 구현이 없습니다.

Tasks

Coreference ResolutionSemantic Textual Similarity

Similar Papers 제목 키워드 기반

Why do objects have many names? A study on word informativeness in language use and lexical systems

2024-10-10 · Eleonora Gualdoni, Gemma Boleda

Human lexicons contain many different words that speakers can use to refer to the same object, e.g., "purple" or "magenta" for the same shade of color. On the one hand, studies on language use have explored how speakers …

Informativeness

Competition in Cross-situational Word Learning: A Computational Study

2020-12-06 · Aida Nematzadeh, Zahra Shekarchi, Thomas L. Griffiths, Suzanne Stevenson

Children learn word meanings by tapping into the commonalities across different situations in which words are used and overcome the high level of uncertainty involved in early word learning experiences. We propose a mode…

Sampling strategies in Siamese Networks for unsupervised speech representation learning

2018-04-30 · Rachid Riad, Corentin Dancette, Julien Karadayi, Neil Zeghidour 외

Recent studies have investigated siamese network architectures for learning invariant speech representations using same-different side information at the word level. Here we investigate systematically an often ignored co…

Representation LearningSpeech Representation Learning

Unsupervised Parallel Sentence Extraction with Parallel Segment Detection Helps Machine Translation

2019-07-01 · ACL 2019 7 · Viktor Hangya, Alex Fraser, er

Mining parallel sentences from comparable corpora is important. Most previous work relies on supervised systems, which are trained on parallel data, thus their applicability is problematic in low-resource scenarios. Rece…

Machine TranslationSentenceTranslationWord Embeddings

A Neural Network Architecture for Learning Word-Referent Associations in Multiple Contexts

2019-05-20 · Hansenclever F. Bassani, Aluizio F. R. Araujo

This article proposes a biologically inspired neurocomputational architecture which learns associations between words and referents in different contexts, considering evidence collected from the literature of Psycholingu…