Canonical Correlation Analysis

We present a method for learning bilingual translation lexicons from monolingual cor- pora. Word types in each language are charac- terized by purely monolingual features, such as context counts and …...

The distributional hypothesis of Harris (1954), according to which the meaning of words is evidenced by the contexts they occur in, has motivated several effec- tive techniques for obtaining vector …...

This paper describes an approach for au- tomatic construction of dictionaries for Named Entity Recognition (NER) using large amounts of unlabeled data and a few seed examples. We use Canonical …...

Word embeddings have been found useful for many NLP tasks, including part-of-speech tagging, named entity recognition, and pars- ing. Adding multilingual context when learn- ing embeddings can improve their quality, …...

This work focuses on the task of finding latent vector representations of the words in a corpus. In particular, we address the issue of what to do when there are …...

AbstractMany of the world’s languages employ grammatical gender on the lexeme. For instance, in Spanish, house “casa” is feminine, whereas the word for paper “papel” is masculine. To a speaker …...

AbstractWe seek to understand how the representations of individual tokens and the structure of the learned feature space evolve between layers in deep neural networks under different learning objectives. We …...

AbstractIn this paper, we describe our method for detection of lexical semantic change, i.e., word sense changes over time. We examine semantic differences between specific words in two corpora, chosen …...