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: "pca lda approach for text independent speaker recognition"
  Abstract: Various algorithms for text-independent speaker recognition have been developed through the decades, aiming#R##N#to improve both accuracy and efficiency. This paper presents a novel PCA/LDA-based approach that is faster#R##N#than traditional statistical model-based methods and achieves competitive results. First, the performance based#R##N#on only PCA and only LDA is measured; then a mixed model, taking advantages of both methods, is introduced.#R##N#A subset of the TIMIT corpus composed of 200 male speakers, is used for enrollment, validation and testing.#R##N#The best results achieve 100%, 96% and 95% classification rate at population level 50, 100 and 200, using 39-#R##N#dimensional MFCC features with delta and double delta. These results are based on 12-second text-independent#R##N#speech for training and 4-second data for test. These are comparable to the conventional MFCC-GMM methods,#R##N#but require significantly less time to train and operate.

Connected through hyperedge HE-1 (induced by source paper "accent classification with phonetic vowel representation"):
  with members:
    - "pca method for automated detection of mispronounced words"
    - "speech recognition with deep recurrent neural networks"

Connected through hyperedge HE-2 (induced by source paper "improved accent classification combining phonetic vowels with acoustic features"):
  with members:
    - "pca method for automated detection of mispronounced words"
    - "accent classification with phonetic vowel representation"

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)