Detecting Unseen Multiword Expressions in American Sign Language
Lee Kezar Aryan Shukla
Multiword expressions present unique challenges in many translation tasks. In
an attempt to ultimately apply a multiword expression detection system to the
translation of American Sign Language, we built and tested two systems that
apply word embeddings from GloVe to determine whether or not the word
embeddings of lexemes can be used to predict whether or not those lexemes
compose a multiword expression. It became apparent that word embeddings carry
data that can detect non-compositionality with decent accuracy.