Formal languages and automata theory are very important for handling and understanding real languages.  This paper discuss about basic automata models, such as finite automata and finite-state transducers, and how they can be used in morphological analysis, tokenization, and lexical analysis. The paper also focuses how these old techniques can be combined with natural language processing methods. In particular, it focusses on mixed models that use automata theory and machine learning to make things more accurate and quick.  The part automata theory plays in formal checking and explaining NLP models is also looked at, shows how important it is for making systems that are clear and dependable.