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 "cat crf based asr toolkit"):
  Abstract: In this paper, we present a new open source toolkit for automatic speech recognition (ASR), named CAT (CRF-based ASR Toolkit). A key feature of CAT is discriminative training in the framework of conditional random field (CRF), particularly with connectionist temporal classification (CTC) inspired state topology. CAT contains a full-fledged implementation of CTC-CRF and provides a complete workflow for CRF-based end-to-end speech recognition. Evaluation results on Chinese and English benchmarks such as Switchboard and Aishell show that CAT obtains the state-of-the-art results among existing end-to-end models with less parameters, and is competitive compared with the hybrid DNN-HMM models. Towards flexibility, we show that i-vector based speaker-adapted recognition and latency control mechanism can be explored easily and effectively in CAT. We hope CAT, especially the CRF-based framework and software, will be of broad interest to the community, and can be further explored and improved.

Includes members:
  Member "rwth asr systems for librispeech hybrid vs attention w o data augmentation":
    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 "espnet end to end speech processing toolkit":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "end to end automatic speech recognition integrated with ctc based voice activity detection")
  Member "fully convolutional speech recognition":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "scaling up online speech recognition using convnets")
  Member "returnn as a generic flexible neural toolkit with application to translation and speech recognition":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "espresso a fast end to end neural speech recognition toolkit")
  Member "wav2letter the fastest open source speech recognition system":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "sequence to sequence speech recognition with time depth separable convolutions")
  Member "improved training of end to end attention models for speech recognition":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "scaling up online speech recognition using convnets")
  Member "monotonic chunkwise attention":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "efficient content based sparse attention with routing transformers")
  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-8 (induced by source paper "end to end automatic speech recognition integrated with ctc based voice activity detection")

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.LG(Machine Learning)