Word Embedding

A technique in natural language processing that represents words as numerical vectors in a multi-dimensional space, where words with similar meanings are positioned closer together. Word embeddings enable computers to understand semantic relationships between words, which supports accessibility applications like automatic text simplification, content summarization for cognitive accessibility, and generating meaningful labels or descriptions. Models like Word2Vec, GloVe, and those underlying BERT use word embeddings as foundational components.