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 "the conversation deep audio visual speech enhancement"):
  Abstract: Our goal is to isolate individual speakers from multi-talker simultaneous speech in videos. Existing works in this area have focussed on trying to separate utterances from known speakers in controlled environments. In this paper, we propose a deep audio-visual speech enhancement network that is able to separate a speaker's voice given lip regions in the corresponding video, by predicting both the magnitude and the phase of the target signal. The method is applicable to speakers unheard and unseen during training, and for unconstrained environments. We demonstrate strong quantitative and qualitative results, isolating extremely challenging real-world examples.

Includes members:
  Member "end to end audiovisual speech recognition":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "lipreading using temporal convolutional networks")
  Member "looking to listen at the cocktail party a speaker independent audio visual model for speech separation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the state of service robots current bottlenecks in object perception and manipulation")
  Member "improved speech reconstruction from silent video":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "mobivsr a visual speech recognition solution for mobile devices")
  Member "supervised speech separation based on deep learning an overview":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "temporal spatial neural filter direction informed end to end multi channel target speech separation")
  Member "visual speech enhancement":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "audio visual speech enhancement using conditional variational auto encoder")
  Member "seeing through noise visually driven speaker separation and enhancement":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "the sound of motions")
  Member "does phase matter for monaural source separation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "end to end music source separation is it possible in the waveform domain")
  Member "lipnet end to end sentence level lipreading":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "can we read speech beyond the lips rethinking roi selection for deep visual speech recognition")

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.CV(Computer Vision and Pattern Recognition)