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 "disfluencies and human speech transcription errors"):
  Abstract: This paper explores contexts associated with errors in transcrip-tion of spontaneous speech, shedding light on human perceptionof disfluencies and other conversational speech phenomena. Anew version of the Switchboard corpus is provided with disfluency annotations for careful speech transcripts, together with results showing the impact of transcription errors on evaluation of automatic disfluency detection.

Includes members:
  Member "giving attention to the unexpected using prosody innovations in disfluency detection":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "multi task self supervised learning for disfluency detection")
  Member "robust cross domain disfluency detection with pattern match networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multi task self supervised learning for disfluency detection")
  Member "english conversational telephone speech recognition by humans and machines":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "distributed training of deep neural network acoustic models for automatic speech recognition")
  Member "parsing speech a neural approach to integrating lexical and acoustic prosodic information":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "identification of primary and collateral tracks in stuttered speech")
  Member "comparing human and machine errors in conversational speech transcription":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "improving oov detection and resolution with external language models in acoustic to word asr")
  Member "disfluency detection using a bidirectional lstm":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "identification of primary and collateral tracks in stuttered speech")
  Member "achieving human parity in conversational speech recognition":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a survey of adversarial learning on graphs")

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)