N-gram Language Models

An n-gram language model is a type of language model that predicts the probability of the next word in a sequence based on a fixed window of previous words. The size of the window depends on the specific n-gram model being used. These models can be estimated using frequency counts from a text corpus, but may require smoothing techniques to handle sparsity. However, n-gram models are not commonly used in modern natural language processing research and applications, as they have been replaced by deep learning methods such as large language models.