Abstract Automatic Speech Recognition (ASR) systems can be trained to achieve
remarkable performance given large amounts of manually transcribed speech, but large …

Cross-lingual word vectors are typically obtained by fitting an orthogonal matrix that maps
the entries of a bilingual dictionary from a source to a target vector space. Word vectors …

Abstract Landgrebe and Smith (Synthese 198 (March): 2061–2081, 2021) present an
unflattering diagnosis of recent advances in what they call language-centric artificial …

Recent studies have proposed different methods to improve multilingual word
representations in contextualized settings including techniques that align between source …

Inducing multilingual word embeddings by learning a linear map between embedding
spaces of different languages achieves remarkable accuracy on related languages …

Word embeddings are crucial to many natural language processing tasks. The quality of
embeddings relies on large non-noisy corpora. Arabic dialects lack large corpora and are …

Abstract Language encoders encode words and phrases in ways that capture their local
semantic relatedness, but are known to be globally inconsistent. Global inconsistency can …

We present LESSLEX, a novel multilingual lexical resource. Different from the vast majority
of existing approaches, we ground our embeddings on a sense inventory made available …

Bilingual lexicons form a critical component of various natural language processing
applications, including unsupervised and semisupervised machine translation and …