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 "scaling up online speech recognition using convnets"):
  Abstract: We design an online end-to-end speech recognition system based on Time-Depth Separable (TDS) convolutions and Connectionist Temporal Classification (CTC). We improve the core TDS architecture in order to limit the future context and hence reduce latency while maintaining accuracy. The system has almost three times the throughput of a well tuned hybrid ASR baseline while also having lower latency and a better word error rate. Also important to the efficiency of the recognizer is our highly optimized beam search decoder. To show the impact of our design choices, we analyze throughput, latency, accuracy, and discuss how these metrics can be tuned based on the user requirements.

Includes members:
  Member "reducing transformer depth on demand with structured dropout":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "rethinking batch normalization in transformers")
  Member "rnn t for latency controlled asr with improved beam search":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "accelerating rnn transducer inference via one step constrained beam search")
  Member "a comparative study on transformer vs rnn in speech applications":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a simplified fully quantized transformer for end to end speech recognition")
  Member "end to end asr from supervised to semi supervised learning with modern architectures":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "learning robust and multilingual speech representations")
  Member "transformer based acoustic modeling for hybrid speech recognition":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "effectiveness of self supervised pre training for speech recognition")
  Member "streaming end to end speech recognition for mobile devices":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a simplified fully quantized transformer for end to end speech recognition")
  Member "fully convolutional speech recognition":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "espresso a fast end to end neural speech recognition toolkit")
  Member "efficient neural audio synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "what is the state of neural network pruning")

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)