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 "multi speaker end to end speech synthesis"):
  Abstract: In this work, we extend ClariNet (Ping et al., 2019), a fully end-to-end speech synthesis model (i.e., text-to-wave), to generate high-fidelity speech from multiple speakers. To model the unique characteristic of different voices, low dimensional trainable speaker embeddings are shared across each component of ClariNet and trained together with the rest of the model. We demonstrate that the multi-speaker ClariNet outperforms state-of-the-art systems in terms of naturalness, because the whole model is jointly optimized in an end-to-end manner.

Includes members:
  Member "parallel neural text to speech":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "waveflow a compact flow based model for raw audio")
  Member "libritts a corpus derived from librispeech for text to speech":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "comparison of speech representations for automatic quality estimation in multi speaker text to speech synthesis")
  Member "neural voice cloning with a few samples":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "speech2phone a multilingual and text independent speaker identification model")
  Member "clarinet parallel wave generation in end to end text to speech":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a neural vocoder with hierarchical generation of amplitude and phase spectra for statistical parametric speech synthesis")
  Member "voiceloop voice fitting and synthesis via a phonological loop":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "unpaired image to speech synthesis with multimodal information bottleneck")
  Member "deep voice real time 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 "tacotron towards end to end speech synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "semi supervised neural architecture search")
  Member "deep voice 3 2000 speaker neural text to speech":
    also connected through other hyperedges:
      - Hyperedge HE-8 (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.CL(Computation and Language)