human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "the microsoft 2017 conversational speech recognition system"):
  Abstract: We describe the 2017 version of Microsoft's conversational speech recognition system, in which we update our 2016 system with recent developments in neural-network-based acoustic and language modeling to further advance the state of the art on the Switchboard speech recognition task. The system adds a CNN-BLSTM acoustic model to the set of model architectures we combined previously, and includes character-based and dialog session aware LSTM language models in rescoring. For system combination we adopt a two-stage approach, whereby subsets of acoustic models are first combined at the senone/frame level, followed by a word-level voting via confusion networks. We also added a confusion network rescoring step after system combination. The resulting system yields a 5.1\% word error rate on the 2000 Switchboard evaluation set.

Includes members:
  Member "english conversational telephone speech recognition by humans and machines":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "distributed training of deep neural network acoustic models for automatic speech recognition")
  Member "comparing human and machine errors in conversational speech transcription":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "improving oov detection and resolution with external language models in acoustic to word asr")
  Member "the ibm 2016 english conversational telephone speech recognition system":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "character level recurrent neural networks in practice comparing training and sampling schemes")
  Member "the microsoft 2016 conversational speech recognition system":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "accelerating rnn transducer inference via one step constrained beam search")
  Member "using the output embedding to improve language models":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "meta embeddings based on self attention")
  Member "achieving human parity in conversational speech recognition":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a survey of adversarial learning on graphs")
  Member "very deep multilingual convolutional neural networks for lvcsr":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "hydra preserving ensemble diversity for model distillation")
  Member "fast and accurate recurrent neural network acoustic models for speech recognition":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "small footprint open vocabulary keyword spotting with quantized lstm networks")

Question: Please tell me which class the source paper 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)