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: "towards end to end prosody transfer for expressive speech synthesis with tacotron"
  Abstract: We present an extension to the Tacotron speech synthesis architecture that learns a latent embedding space of prosody, derived from a reference acoustic representation containing the desired prosody. We show that conditioning Tacotron on this learned embedding space results in synthesized audio that matches the prosody of the reference signal with fine time detail even when the reference and synthesis speakers are different. Additionally, we show that a reference prosody embedding can be used to synthesize text that is different from that of the reference utterance. We define several quantitative and subjective metrics for evaluating prosody transfer, and report results with accompanying audio samples from single-speaker and 44-speaker Tacotron models on a prosody transfer task.

Connected through hyperedge HE-1 (induced by source paper "et gan cross language emotion transfer based on cycle consistent generative adversarial networks"):
  with members:
    - "cyclegan vc2 improved cyclegan based non parallel voice conversion"
    - "talking face generation by adversarially disentangled audio visual representation"
    - "voxceleb2 deep speaker recognition"
    - "voxceleb a large scale speaker identification dataset"
    - "unpaired image to image translation using cycle consistent adversarial networks"
    - "emotional end to end neural speech synthesizer"
    - "cnn architectures for large scale audio classification"
    - "language modeling with gated convolutional networks"

Connected through hyperedge HE-2 (induced by source paper "interactive text to speech via semi supervised style transfer learning"):
  with members:
    - "visualization and interpretation of latent spaces for controlling expressive speech synthesis through audio analysis"
    - "challenging common assumptions in the unsupervised learning of disentangled representations"
    - "multimodal speech emotion recognition using audio and text"
    - "attention is all you need"
    - "uncovering latent style factors for expressive speech synthesis"
    - "wavenet a generative model for raw audio"
    - "neural machine translation by jointly learning to align and translate"

Connected through hyperedge HE-3 (induced by source paper "espnet tts unified reproducible and integratable open source end to end text to speech toolkit"):
  with members:
    - "fastspeech fast robust and controllable text to speech"
    - "jvs corpus free japanese multi speaker voice corpus"
    - "libritts a corpus derived from librispeech for text to speech"
    - "mixed precision training for nlp and speech recognition with openseq2seq"
    - "back translation style data augmentation for end to end asr"
    - "waveglow a flow based generative network for speech synthesis"
    - "espnet end to end speech processing toolkit"
    - "close to human quality tts with transformer"

Connected through hyperedge HE-4 (induced by source paper "semi supervised generative modeling for controllable speech synthesis"):
  with members:
    - "effective use of variational embedding capacity in expressive end to end speech synthesis"
    - "fastspeech fast robust and controllable text to speech"
    - "chive varying prosody in speech synthesis with a linguistically driven dynamic hierarchical conditional variational network"
    - "efficient neural audio synthesis"
    - "style tokens unsupervised style modeling control and transfer in end to end speech synthesis"
    - "expressive speech synthesis via modeling expressions with variational autoencoder"
    - "hierarchical generative modeling for controllable speech synthesis"
    - "voiceloop voice fitting and synthesis via a phonological loop"

Connected through hyperedge HE-5 (induced by source paper "m3d gan multi modal multi domain translation with universal attention"):
  with members:
    - "style tokens unsupervised style modeling control and transfer in end to end speech synthesis"
    - "the unreasonable effectiveness of deep features as a perceptual metric"
    - "the microsoft 2017 conversational speech recognition system"
    - "attention is all you need"
    - "unpaired image to image translation using cycle consistent adversarial networks"
    - "toward multimodal image to image translation"
    - "stargan unified generative adversarial networks for multi domain image to image translation"
    - "one sided unsupervised domain mapping"

Connected through hyperedge HE-6 (induced by source paper "effective use of variational embedding capacity in expressive end to end speech synthesis"):
  with members:
    - "location relative attention mechanisms for robust long form speech synthesis"
    - "predicting expressive speaking style from text in end to end speech synthesis"
    - "learning latent representations for style control and transfer in end to end speech synthesis"
    - "robust and fine grained prosody control of end to end speech synthesis"
    - "hierarchical generative modeling for controllable speech synthesis"
    - "voiceloop voice fitting and synthesis via a phonological loop"
    - "fixing a broken elbo"
    - "tacotron towards end to end speech synthesis"

Connected through hyperedge HE-7 (induced by source paper "adversarially trained end to end korean singing voice synthesis system"):
  with members:
    - "cgans with projection discriminator"
    - "spectral normalization for generative adversarial networks"
    - "style tokens unsupervised style modeling control and transfer in end to end speech synthesis"
    - "large scale gan training for high fidelity natural image synthesis"
    - "which training methods for gans do actually converge"
    - "semi supervised training for improving data efficiency in end to end speech synthesis"
    - "efficiently trainable text to speech system based on deep convolutional networks with guided attention"
    - "tacotron towards end to end speech synthesis"

Connected through hyperedge HE-8 (induced by source paper "one shot voice conversion by separating speaker and content representations with instance normalization"):
  with members:
    - "gansynth adversarial neural audio synthesis"
    - "stargan vc non parallel many to many voice conversion with star generative adversarial networks"
    - "machine speech chain with one shot speaker adaptation"
    - "style tokens unsupervised style modeling control and transfer in end to end speech synthesis"
    - "rhythm flexible voice conversion without parallel data using cycle gan over phoneme posteriorgram sequences"
    - "voice conversion using sequence to sequence learning of context posterior probabilities"
    - "arbitrary style transfer in real time with adaptive instance normalization"
    - "tacotron towards end to end speech synthesis"

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.CL(Computation and Language)