Ngrammi

Ngrammi is a term that refers to n-grams, which are contiguous sequences of n items from a given sample of text or speech. In natural language processing and computational linguistics, an n-gram is a sample of contiguous elements from a given sample of text or speech. The elements can be considered phonemes, syllables, letters, or words, depending on the application. For instance, an n-gram of size 1 is a unigram, size 2 is a bigram, size 3 is a trigram, and so on.

Unigrams are individual words. Bigrams are pairs of consecutive words. Trigrams are sequences of three consecutive words. The concept of n-grams is widely used in various language processing tasks. For example, in language modeling, n-grams are used to predict the next word in a sequence based on the preceding n-1 words. This is achieved by calculating the probability of a word appearing given the previous words, typically using frequencies from a large corpus of text.

N-gram models are essential for tasks like speech recognition, machine translation, spelling correction, and text generation. They help capture the statistical regularities and dependencies within a language. The choice of n, the size of the n-gram, is a trade-off between capturing more context and the sparsity of data. Larger values of n can provide more context but require larger datasets to estimate probabilities reliably, as many possible n-grams may not appear in the training data. Techniques like smoothing are often employed to address the issue of unseen n-grams.