human: Given a node-centered hypergraph: <hypergraph>, where nodes represent authors and hyperedges represent groups of authors who co-authored the same paper.

Details of the hypergraph:
Center node: "Evaluation of Real-time Voice Activity Detection based on High Order Statistics"
  Abstract: We have proposed a method for real-time, unsupervised voice activity detection (VAD). In this paper, problems of feature selection and classification scheme are addressed. The feature is based on High Order Statistics (HOS) to discriminate close and far-field talk, enhanced by a feature derived from the normalized autocorrelation. Comparative effectiveness on several HOS is shown. The classification is done in real-time with a recursive, online EM algorithm. The algorithm is evaluated on the CENSREC-1-C database, which is used for VAD evaluation for automatic speech recognition (ASR) [1], and the proposed method is confirmed to significantly outperform the baseline energy-based method. Index Terms: Voice activity detection, online EM, high order statistics

Connected through hyperedge HE-1 (induced by source paper "On-line EM Algorithm for the Normalized Gaussian Network"):
  with members:
    - "Online Model Selection Based on the Variational Bayes"
    - "An Empirical Comparison of Bayesian Network Parameter Learning Algorithms for Continuous Data Streams"

Question: Please tell me which research area the center author belongs to. The 4 classes are: Computer science, Mathematics, Engineering, Economics, Psychology, Business. Directly output the class name.

gpt: Computer science