you might enjoy this read, which is an up-to-date document from this year laying out what was the state of the art 20 years ago: https://web.stanford.edu/~jura

you might enjoy this read, which is an up-to-date document from this year laying out what was the state of the art 20 years ago: https://web.stanford.edu/~jurafsky/slp3/3.pdf https://web.stanford.edu/~jurafsky/slp3/3.pdf Essentially you just count every n-gram that's actually in the corpus, and "fill in the blanks" for all the 0s with some simple rules for smoothing out the probability.