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: "a robust diarization system for measuring dominance in peer led team learning groups"
  Abstract: Peer-Led Team Learning (PLTL) is a structured learning model where a team leader is appointed to facilitate collaborative problem solving among students for Science, Technology, Engineering and Mathematics (STEM) courses. This paper presents an informed HMM-based speaker diarization system. The minimum duration of short conversationalturns and number of participating students were fed as side information to the HMM system. A modified form of Bayesian Information Criterion (BIC) was used for iterative merging and re-segmentation. Finally, we used the diarization output to compute a novel dominance score based on unsupervised acoustic analysis.

Connected through hyperedge HE-1 (induced by source paper "toeplitz inverse covariance based robust speaker clustering for naturalistic audio streams"):
  with members:
    - "robust speaker clustering using mixtures of von mises fisher distributions for naturalistic audio streams"
    - "robust feature clustering for unsupervised speech activity detection"
    - "using speech technology for quantifying behavioral characteristics in peer led team learning sessions"
    - "toeplitz inverse covariance based clustering of multivariate time series data"
    - "a speaker diarization system for studying peer led team learning groups"

Connected through hyperedge HE-2 (induced by source paper "robust speaker clustering using mixtures of von mises fisher distributions for naturalistic audio streams"):
  with members:
    - "robust feature clustering for unsupervised speech activity detection"
    - "using speech technology for quantifying behavioral characteristics in peer led team learning sessions"
    - "a speaker diarization system for studying peer led team learning groups"

Connected through hyperedge HE-3 (induced by source paper "using speech technology for quantifying behavioral characteristics in peer led team learning sessions"):
  with members:
    - "a speaker diarization system for studying peer led team learning groups"

Connected through hyperedge HE-4 (induced by source paper "harmonic sum based method for heart rate estimation using ppg signals affected with motion artifacts"):
  with members:
    - "a speaker diarization system for studying peer led team learning groups"
    - "fit a fog computing device for speech teletreatments"
    - "echowear smartwatch technology for voice and speech treatments of patients with parkinson s disease"
    - "a multi smartwatch system for assessing speech characteristics of people with dysarthria in group settings"
    - "photoplethysmography based heart rate monitoring in physical activities via joint sparse spectrum reconstruction"
    - "troika a general framework for heart rate monitoring using wrist type photoplethysmographic signals during intensive physical exercise"
    - "fog data enhancing telehealth big data through fog computing"

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)