Finite state automata and transducers are computational models that were widely used decades before in natural language processing for morphological parsing and other nlp tasks. I wonder if these computational models are still used in NLP nowadays for significant purposes. If these models are in use, can you give me some examples ?
Both are used, for example, in the GATE framework, which is still widely used. I suspect that this also applies to many other applications.
I would think that many recent academic publications are now on other approaches, as FSAs and FSTs are fairly established and mature technologies, but I've been out of academia for a while now.