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: "the state of speech in hci trends themes and challenges"
  Abstract: Speech interfaces are growing in popularity. Through a review of 68 research papers this work maps the trends, themes, findings and methods of empirical research on speech interfaces in HCI. We find that most studies are usability/theory-focused or explore wider system experiences, evaluating Wizard of Oz, prototypes, or developed systems by using self-report questionnaires to measure concepts like usability and user attitudes. A thematic analysis of the research found that speech HCI work focuses on nine key topics: system speech production, modality comparison, user speech production, assistive technology \& accessibility, design insight, experiences with interactive voice response (IVR) systems, using speech technology for development, people's experiences with intelligent personal assistants (IPAs) and how user memory affects speech interface interaction. From these insights we identify gaps and challenges in speech research, notably the need to develop theories of speech interface interaction, grow critical mass in this domain, increase design work, and expand research from single to multiple user interaction contexts so as to reflect current use contexts. We also highlight the need to improve measure reliability, validity and consistency, in the wild deployment and reduce barriers to building fully functional speech interfaces for research.

Connected through hyperedge HE-1 (induced by source paper "unmet needs and opportunities for mobile translation ai"):
  with members:
    - "joint modeling of accents and acoustics for multi accent speech recognition"
    - "sequence to sequence models can directly translate foreign speech"

Connected through hyperedge HE-2 (induced by source paper "mapping perceptions of humanness in intelligent personal assistant interaction"):
  with members:
    - "what makes a good conversation challenges in designing truly conversational agents"
    - "a survey investigating usage of virtual personal assistants"
    - "expressive speech synthesis via modeling expressions with variational autoencoder"

Connected through hyperedge HE-3 (induced by source paper "multitasking with alexa how using intelligent personal assistants impacts language based primary task performance"):
  with members:
    - "what makes a good conversation challenges in designing truly conversational agents"
    - "a survey investigating usage of virtual personal assistants"
    - "wavenet a generative model for raw audio"

Connected through hyperedge HE-4 (induced by source paper "what s in an accent the impact of accented synthetic speech on lexical choice in human machine dialogue"):
  with members:
    - "what makes a good conversation challenges in designing truly conversational agents"
    - "is spoken language all or nothing implications for future speech based human machine interaction"

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.HC(Human-Computer Interaction)