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 "on using specaugment for end to end speech translation"):
  Abstract: This work investigates a simple data augmentation technique, SpecAugment, for end-to-end speech translation. SpecAugment is a low-cost implementation method applied directly to the audio input features and it consists of masking blocks of frequency channels, and/or time steps. We apply SpecAugment on end-to-end speech translation tasks and achieve up to +2.2\% \BLEU on LibriSpeech Audiobooks En->Fr and +1.2% on IWSLT TED-talks En->De by alleviating overfitting to some extent. We also examine the effectiveness of the method in a variety of data scenarios and show that the method also leads to significant improvements in various data conditions irrespective of the amount of training data.

Includes members:
  Member "a comparative study on end to end speech to text translation":
    also connected through other hyperedges:
      (none)
  Member "on using 2d sequence to sequence models for speech recognition":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a comparative study on end to end speech to text translation")
  Member "end to end speech translation with knowledge distillation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multilingual end to end speech translation")
  Member "augmenting librispeech with french translations a multimodal corpus for direct speech translation evaluation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "covost a diverse multilingual speech to text translation corpus")
  Member "towards unsupervised speech to text translation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "representation learning for electronic health records")
  Member "end to end automatic speech translation of audiobooks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "covost a diverse multilingual speech to text translation corpus")
  Member "leveraging weakly supervised data to improve end to end speech to text translation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "multilingual end to end speech translation")
  Member "improved training of end to end attention models for speech recognition":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "scaling up online speech recognition using convnets")

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)