human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "application of fuzzy mathematics to speech to text conversion by elimination of paralinguistic content"
  Abstract: For the past few decades, man has been trying to create an intelligent computer which can talk and respond like he can. The task of creating a system that can talk like a human being is the primary objective of Automatic Speech Recognition. Various Speech Recognition techniques have been developed in theory and have been applied in practice. This paper discusses the problems that have been encountered in developing Speech Recognition, the techniques that have been applied to automate the task, and a representation of the core problems of present day Speech Recognition by using Fuzzy Mathematics.

Connected through hyperedge HE-1 (induced by source paper "representation of a sentence using a polar fuzzy neutrosophic semantic net"):
  with members:
    - "applicability of crisp and fuzzy logic in intelligent response generation"

Connected through hyperedge HE-2 (induced by source paper "applicability of crisp and fuzzy logic in intelligent response generation"):
  with members:
    - "a neuro fuzzy technique for implementing the half adder circuit using the canfis model"
    - "speech signal filters based on soft computing techniques a comparison"

Connected through hyperedge HE-3 (induced by source paper "the future of neural networks"):
  with members:
    - "a neuro fuzzy technique for implementing the half adder circuit using the canfis model"
    - "speech signal filters based on soft computing techniques a comparison"

Connected through hyperedge HE-4 (induced by source paper "speech signal filters based on soft computing techniques a comparison"):
  with members:
    - "a neuro fuzzy technique for implementing the half adder circuit using the canfis model"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.AI(Artificial Intelligence)