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: "complex nmf under phase constraints based on signal modeling application to audio source separation"
  Abstract: Nonnegative Matrix Factorization (NMF) is a powerful tool for decomposing mixtures of audio signals in the Time-Frequency (TF) domain. In the source separation framework, the phase recovery for each extracted component is necessary for synthesizing time-domain signals. The Complex NMF (CNMF) model aims to jointly estimate the spectrogram and the phase of the sources, but requires to constrain the phase in order to produce satisfactory sounding results. We propose to incorporate phase constraints based on signal models within the CNMF framework: a phase unwrapping constraint that enforces a form of temporal coherence, and a constraint based on the repetition of audio events, which models the phases of the sources within onset frames. We also provide an algorithm for estimating the model parameters. The experimental results highlight the interest of including such constraints in the CNMF framework for separating overlapping components in complex audio mixtures.

Connected through hyperedge HE-1 (induced by source paper "complex isnmf a phase aware model for monaural audio source separation"):
  with members:
    - "multi scale multi band densenets for audio source separation"
    - "phase reconstruction of spectrograms with linear unwrapping application to audio signal restoration"
    - "model based stft phase recovery for audio source separation"
    - "phase recovery in nmf for audio source separation an insightful benchmark"

Connected through hyperedge HE-2 (induced by source paper "svsgan singing voice separation via generative adversarial network"):
  with members:
    - "segan speech enhancement generative adversarial network"
    - "image to image translation with conditional adversarial networks"

Connected through hyperedge HE-3 (induced by source paper "model based stft phase recovery for audio source separation"):
  with members:
    - "multi scale multi band densenets for audio source separation"
    - "phase reconstruction of spectrograms with linear unwrapping application to audio signal restoration"
    - "single channel multi speaker separation using deep clustering"
    - "phase reconstruction of spectrograms based on a model of repeated audio events"
    - "phase recovery in nmf for audio source separation an insightful benchmark"
    - "informed source separation using iterative reconstruction"
    - "wirtinger s calculus in general hilbert spaces"

Connected through hyperedge HE-4 (induced by source paper "phase recovery by unwrapping applications to music signal processing"):
  with members:
    - "multi scale multi band densenets for audio source separation"
    - "phase reconstruction of spectrograms with linear unwrapping application to audio signal restoration"
    - "phase reconstruction of spectrograms based on a model of repeated audio events"
    - "phase recovery in nmf for audio source separation an insightful benchmark"
    - "wirtinger s calculus in general hilbert spaces"

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.SD(Sound)