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 "automated screening for distress a perspective for the future"):
  Abstract: Distress is a complex condition which affects a significant percentage of cancer patients and may lead to depression, anxiety, sadness, suicide and other forms of psychological morbidity. Compelling evidence supports screening for distress as a means of facilitating early intervention and subsequent improvements in psychological well-being and overall quality of life. Nevertheless, despite the existence of evidence based and easily administered screening tools, for example, the Distress Thermometer, routine screening for distress is yet to achieve widespread implementation. Efforts are intensifying to utilise innovative, cost effective methods now available through emerging technologies in the informatics and computational arenas.

Includes members:
  Member "transfer learning for improving speech emotion classification accuracy":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "multi task semi supervised adversarial autoencoding for speech emotion")
  Member "depression scale recognition from audio visual and text analysis":
    also connected through other hyperedges:
      (none)
  Member "variational autoencoders for learning latent representations of speech emotion a preliminary study":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multi task semi supervised adversarial autoencoding for speech emotion")
  Member "avec 2016 depression mood and emotion recognition workshop and challenge":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "deep learning for human affect recognition insights and new developments")
  Member "gait velocity estimation using time interleaved between consecutive passive ir sensor activations":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multi task semi supervised adversarial autoencoding for speech emotion")

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.HC(Human-Computer Interaction)