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 "scene aware audio rendering via deep acoustic analysis"):
  Abstract: We present a new method to capture the acoustic characteristics of real-world rooms using commodity devices, and use the captured characteristics to generate similar sounding sources with virtual models. Given the captured audio and an approximate geometric model of a real-world room, we present a novel learning-based method to estimate its acoustic material properties. Our approach is based on deep neural networks that estimate the reverberation time and equalization of the room from recorded audio. These estimates are used to compute material properties related to room reverberation using a novel material optimization objective. We use the estimated acoustic material characteristics for audio rendering using interactive geometric sound propagation and highlight the performance on many real-world scenarios. We also perform a user study to evaluate the perceptual similarity between the recorded sounds and our rendered audio.

Includes members:
  Member "scenecode monocular dense semantic reconstruction using learned encoded scene representations":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "routedfusion learning real time depth map fusion")
  Member "data augmentation and deep convolutional neural networks for blind room acoustic parameter estimation":
    also connected through other hyperedges:
      (none)
  Member "impulse response data augmentation and deep neural networks for blind room acoustic parameter estimation":
    also connected through other hyperedges:
      (none)
  Member "regression and classification for direction of arrival estimation with convolutional recurrent neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "improving reverberant speech training using diffuse acoustic simulation")
  Member "deeplight learning illumination for unconstrained mobile mixed reality":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "seeing the world in a bag of chips")
  Member "low frequency compensated synthetic impulse responses for improved far field speech recognition":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "improving reverberant speech training using diffuse acoustic simulation")
  Member "improving reverberant speech training using diffuse acoustic simulation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "regression and classification for direction of arrival estimation with convolutional recurrent neural networks")
  Member "scene aware audio for 360 videos":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "semantic object prediction and spatial sound super resolution with binaural sounds")

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.SD(Sound)