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: "the marchex 2018 english conversational telephone speech recognition system"
  Abstract: In this paper, we describe recent improvements to the production Marchex speech recognition system for our spontaneous customer-to-business telephone conversations. We outline our semi-supervised lattice-free maximum mutual information (LF-MMI) training process which can supervise over full lattices from unlabeled audio. We also elaborate on production-scale text selection techniques for constructing very large conversational language models (LMs). On Marchex English (ME), a modern evaluation set of conversational North American English, for acoustic modeling we report a 3.3% ({agent, caller}:{3.2%, 3.6%}) reduction in absolute word error rate (WER). For language modeling, we observe a separate {1.3%, 1.2%} point reduction on {agent, caller} utterances respectively over the performance of the 2017 production system.

Connected through hyperedge HE-1 (induced by source paper "towards better understanding of spontaneous conversations overcoming automatic speech recognition errors with intent recognition"):
  with members:
    - "composing finite state transducers on gpus"
    - "the capio 2017 conversational speech recognition system"
    - "punctuation prediction model for conversational speech"
    - "just ask building an architecture for extensible self service spoken language understanding"
    - "the microsoft 2017 conversational speech recognition system"
    - "encodingword confusion networks with recurrent neural networks for dialog state tracking"
    - "finding consensus in speech recognition word error minimization and other applications of confusion networks"

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.CL(Computation and Language)