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 "learning to speak fluently in a foreign language multilingual speech synthesis and cross language voice cloning"):
  Abstract: We present a multispeaker, multilingual text-to-speech (TTS) synthesis model based on Tacotron that is able to produce high quality speech in multiple languages. Moreover, the model is able to transfer voices across languages, e.g. synthesize fluent Spanish speech using an English speaker's voice, without training on any bilingual or parallel examples. Such transfer works across distantly related languages, e.g. English and Mandarin. #R##N#Critical to achieving this result are: 1. using a phonemic input representation to encourage sharing of model capacity across languages, and 2. incorporating an adversarial loss term to encourage the model to disentangle its representation of speaker identity (which is perfectly correlated with language in the training data) from the speech content. Further scaling up the model by training on multiple speakers of each language, and incorporating an autoencoding input to help stabilize attention during training, results in a model which can be used to consistently synthesize intelligible speech for training speakers in all languages seen during training, and in native or foreign accents.

Includes members:
  Member "unsupervised polyglot text to speech":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "unsupervised singing voice conversion")
  Member "neural voice cloning with a few samples":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "speech2phone a multilingual and text independent speaker identification model")
  Member "efficient neural audio synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "what is the state of neural network pruning")
  Member "representation mixing for tts synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "libritts a corpus derived from librispeech for text to speech")
  Member "sample efficient adaptive text to speech":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "dawson a domain adaptive few shot generation framework")
  Member "learning pronunciation from a foreign language in speech synthesis networks":
    also connected through other hyperedges:
      (none)
  Member "expressive speech synthesis via modeling expressions with variational autoencoder":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "semi supervised generative modeling for controllable speech synthesis")
  Member "fitting new speakers based on a short untranscribed sample":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "unpaired image to speech synthesis with multimodal information bottleneck")

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)