Introduction to NLP with Traditional Language Model : N-grams and Hidden Markov Model (Part II)

Welcome to the second part of the “Introduction to NLP with Traditional Language Models: N-grams and Hidden Markov Models”😊. In the first part, we explored N-grams and their applications in NLP, including some smoothing techniques and examples. You can check it out here: Introduction to NLP with Traditional Language Model : N-grams and Hidden Markov Model (Part I) | by Warren Chris Randhall LATA | Jul, 2024 | Medium.

In this article, we will delve into Hidden Markov Models, covering their essential concepts, examples with calculations, advantages and limitations, and applications. We will also provide a example for speech recognition.

Don’t hesitate to subscribe as i will publish more interesting topics in the coming days. More importantly, don’t hesitate to comment and send me those claps if you like the work done 😂.

2. Hidden Markov Model

So what is a hidden markov model (hmm)? It is a statistical model modelized as markovian processus. If you d’ont know what is a markovian processus no worries i will give you a brief but consistent introduction to understand the principle behind. Just you need to know that, it is a stochastic processus representing the evolution of a discrete or continuous random variable helping to calculate the probability of possible event.

Markovian processus