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 "tracking multiple audio sources with the von mises distribution and variational em"):
  Abstract: In this paper, we address the problem of simultaneously tracking several audio sources, namely the problem of estimating source trajectories from a sequence of the observed features. We propose to use the von Mises distribution to model audio-source directions of arrival (DOAs) with circular random variables. This leads to a multi-target Kalman filter formulation which is intractable because of the combinatorial explosion of associating observations to state variables over time. We propose a variational approximation of the filter's posterior distribution and we infer a variational expectation maximization (VEM) algorithm which is computationally efficient. We also propose an audio-source birth method that favors smooth source trajectories and which is used both to initialize the number of active sources and to detect new sources. We perform experiments with a recently released dataset comprising several moving sources as well as a moving microphone array.

Includes members:
  Member "online localization and tracking of multiple moving speakers in reverberant environments":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "high resolution speaker counting in reverberant rooms using crnn with ambisonics features")
  Member "variational bayesian inference for audio visual tracking of multiple speakers":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "self supervised moving vehicle tracking with stereo sound")
  Member "multiple speaker localization based on direct path features and likelihood maximization with spatial sparsity regularization":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "sinusoidal wave generating network based on adversarial learning and its application synthesizing frog sounds for data augmentation")
  Member "an on line variational bayesian model for multi person tracking from cluttered scenes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "how to train your deep multi object tracker")

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)