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 "introduction to voice presentation attack detection and recent advances"):
  Abstract: Over the past few years significant progress has been made in the field of presentation attack detection (PAD) for automatic speaker recognition (ASV). This includes the development of new speech corpora, standard evaluation protocols and advancements in front-end feature extraction and back-end classifiers. The use of standard databases and evaluation protocols has enabled for the first time the meaningful benchmarking of different PAD solutions. This chapter summarises the progress, with a focus on studies completed in the last three years. The article presents a summary of findings and lessons learned from two ASVspoof challenges, the first community-led benchmarking efforts. These show that ASV PAD remains an unsolved problem and that further attention is required to develop generalised PAD solutions which have potential to detect diverse and previously unseen spoofing attacks.

Includes members:
  Member "generalization of spoofing countermeasures a case study with asvspoof 2015 and btas 2016 corpora":
    also connected through other hyperedges:
      (none)
  Member "attacking speaker recognition with deep generative models":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "hear no evil see kenansville efficient and transferable black box attacks on speech recognition and voice identification systems")
  Member "fooling end to end speaker verification by adversarial examples":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "hear no evil see kenansville efficient and transferable black box attacks on speech recognition and voice identification systems")
  Member "voice conversion using sequence to sequence learning of context posterior probabilities":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "sequence to sequence acoustic modeling for voice conversion")
  Member "a study on replay attack and anti spoofing for automatic speaker verification":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "detecting replay attacks using multi channel audio a neural network based method")
  Member "tacotron towards end to end speech synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "semi supervised neural architecture search")
  Member "deep voice 2 multi speaker neural text to speech":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "unpaired image to speech synthesis with multimodal information bottleneck")
  Member "natural tts synthesis by conditioning wavenet on mel spectrogram predictions":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "semi supervised neural architecture search")

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.SD(Sound)