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 "advancing connectionist temporal classification with attention modeling"):
  Abstract: In this study, we propose advancing all-neural speech recognition by directly incorporating attention modeling within the Connectionist Temporal Classification (CTC) framework. In particular, we derive new context vectors using time convolution features to model attention as part of the CTC network. To further improve attention modeling, we utilize content information extracted from a network representing an implicit language model. Finally, we introduce vector based attention weights that are applied on context vectors across both time and their individual components. We evaluate our system on a 3400 hours Microsoft Cortana voice assistant task and demonstrate that our proposed model consistently outperforms the baseline model achieving about 20% relative reduction in word error rates.

Includes members:
  Member "advancing acoustic to word ctc model":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "speech corpus of ainu folklore and end to end speech recognition for ainu language")
  Member "exploring architectures data and units for streaming end to end speech recognition with rnn transducer":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "accelerating rnn transducer inference via one step constrained beam search")
  Member "direct acoustics to word models for english conversational speech recognition":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "acoustic to word models with conversational context information")
  Member "gram ctc automatic unit selection and target decomposition for sequence labelling":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "guiding ctc posterior spike timings for improved posterior fusion and knowledge distillation")
  Member "advances in joint ctc attention based end to end speech recognition with a deep cnn encoder and rnn lm":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "end to end automatic speech recognition integrated with ctc based voice activity detection")
  Member "exploring neural transducers for end to end speech recognition":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "the architectural implications of facebook s dnn based personalized recommendation")
  Member "improving the performance of online neural transducer models":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "streaming automatic speech recognition with the transformer model")
  Member "neural speech recognizer acoustic to word lstm model for large vocabulary speech recognition":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "deep learning for audio signal processing")

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.CL(Computation and Language)