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 "generating black metal and math rock beyond bach beethoven and beatles"):
  Abstract: We use a modified SampleRNN architecture to generate music in modern genres such as black metal and math rock. Unlike MIDI and symbolic models, SampleRNN generates raw audio in the time domain. This requirement becomes increasingly important in modern music styles where timbre and space are used compositionally. Long developmental compositions with rapid transitions between sections are possible by increasing the depth of the network beyond the number used for speech datasets. We are delighted by the unique characteristic artifacts of neural synthesis.

Includes members:
  Member "midinet a convolutional generative adversarial network for symbolic domain music generation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "music generation by deep learning challenges and directions")
  Member "generating nontrivial melodies for music as a service":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "generating albums with samplernn to imitate metal rock and punk bands")
  Member "deep voice real time neural text to speech":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "unpaired image to speech synthesis with multimodal information bottleneck")
  Member "samplernn an unconditional end to end neural audio generation model":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "ddsp differentiable digital signal processing")
  Member "wavenet a generative model for raw audio":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "noise estimation using density estimation for self supervised multimodal learning")
  Member "deepbach a steerable model for bach chorales generation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "music generation by deep learning challenges and directions")
  Member "empirical evaluation of gated recurrent neural networks on sequence modeling":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "using a thousand optimization tasks to learn hyperparameter search strategies")

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)