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 "semi supervised generative modeling for controllable speech synthesis"):
  Abstract: We present a novel generative model that combines state-of-the-art neural text-to-speech (TTS) with semi-supervised probabilistic latent variable models. By providing partial supervision to some of the latent variables, we are able to force them to take on consistent and interpretable purposes, which previously hasn't been possible with purely unsupervised TTS models. We demonstrate that our model is able to reliably discover and control important but rarely labelled attributes of speech, such as affect and speaking rate, with as little as 1% (30 minutes) supervision. Even at such low supervision levels we do not observe a degradation of synthesis quality compared to a state-of-the-art baseline. Audio samples are available on the web.

Includes members:
  Member "effective use of variational embedding capacity in expressive end to end speech synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "location relative attention mechanisms for robust long form speech synthesis")
  Member "fastspeech fast robust and controllable text to speech":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "semi supervised neural architecture search")
  Member "chive varying prosody in speech synthesis with a linguistically driven dynamic hierarchical conditional variational network":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "improving universal sound separation using sound classification")
  Member "efficient neural audio synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "what is the state of neural network pruning")
  Member "style tokens unsupervised style modeling control and transfer in end to end speech synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "unpaired image to speech synthesis with multimodal information bottleneck")
  Member "expressive speech synthesis via modeling expressions with variational autoencoder":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "in other news a bi style text to speech model for synthesizing newscaster voice with limited data")
  Member "hierarchical generative modeling for controllable speech synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "deterministic decoding for discrete data in variational autoencoders")
  Member "towards end to end prosody transfer for expressive speech synthesis with tacotron":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "et gan cross language emotion transfer based on cycle consistent generative adversarial networks")

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)