Are FSA and FSTs used in NLP nowadays? 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.