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Within the field of Natural Language Processing, slang and colloquial language provide a unique challenge for the training and use of language models. This speech holds an odd, transient space with public consciousness, as each instance has a variable time of relevancy and popularity, amongst other factors such as their fluid definition, usage amongst certain groups, and relative lack of information and training data concerning new or evolving terms. These characteristics make it difficult for models to learn these phrases in a timely manner. This project focuses on how a NLP model could learn new additions to colloquial language in a timely and efficient manner, as well as keep up with a rapidly mutating lexicon.

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Natural Language Processing: Understanding Slang and Colloquial Speech