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: "stc anti spoofing systems for the asvspoof 2015 challenge"
  Abstract: This paper presents the Speech Technology Center (STC) systems submitted to Automatic Speaker Verification Spoofing and Countermeasures (ASVspoof) Challenge 2015. In this work we investigate different acoustic feature spaces to determine reliable and robust countermeasures against spoofing attacks. In addition to the commonly used front-end MFCC features we explored features derived from phase spectrum and features based on applying the multiresolution wavelet transform. Similar to state-of-the-art ASV systems, we used the standard TV-JFA approach for probability modelling in spoofing detection systems. Experiments performed on the development and evaluation datasets of the Challenge demonstrate that the use of phase-related and wavelet-based features provides a substantial input into the efficiency of the resulting STC systems. In our research we also focused on the comparison of the linear (SVM) and nonlinear (DBN) classifiers.

Connected through hyperedge HE-1 (induced by source paper "introduction to voice presentation attack detection and recent advances"):
  with members:
    - "generalization of spoofing countermeasures a case study with asvspoof 2015 and btas 2016 corpora"
    - "attacking speaker recognition with deep generative models"
    - "fooling end to end speaker verification by adversarial examples"
    - "voice conversion using sequence to sequence learning of context posterior probabilities"
    - "a study on replay attack and anti spoofing for automatic speaker verification"
    - "tacotron towards end to end speech synthesis"
    - "deep voice 2 multi speaker neural text to speech"
    - "natural tts synthesis by conditioning wavenet on mel spectrogram predictions"

Connected through hyperedge HE-2 (induced by source paper "detecting spoofing attacks using vgg and sincnet but omilia submission to asvspoof 2019 challenge"):
  with members:
    - "a light cnn for deep face representation with noisy labels"
    - "very deep convolutional networks for large scale image recognition"

Connected through hyperedge HE-3 (induced by source paper "voice spoofing detection corpus for single and multi order audio replays"):
  with members:
    - "remasc realistic replay attack corpus for voice controlled systems"

Connected through hyperedge HE-4 (induced by source paper "audio replay attack detection countermeasures"):
  with members:
    - "a light cnn for deep face representation with noisy labels"
    - "going deeper with convolutions"
    - "empirical evaluation of gated recurrent neural networks on sequence modeling"
    - "learn convolutional neural network for face anti spoofing"
    - "network in network"
    - "representation learning a review and new perspectives"

Connected through hyperedge HE-5 (induced by source paper "anti spoofing methods for automatic speakerverification system"):
  with members:
    - "the sysu system for the interspeech 2015 automatic speaker verification spoofing and countermeasures challenge"

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.SD(Sound)