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 "interactive text to speech via semi supervised style transfer learning"):
  Abstract: With increasing interests in interactive speech systems, speech emotion recognition and multi-style text-to-speech (TTS) synthesis are becoming increasingly important research areas. In this paper, we combine both. We present a method to extract speech style embed-dings from input speech queries and apply this embedding as conditional input to a TTS voice so that the TTS response matches the speaking style of the input query. Specifically, we first train a multi-modal style classification model using acoustic and textual features of speech utterances. Due to a limited amount of labeled data, we combined the emotional recognition dataset: the interactive emotional dyadic motion capture database (IEMOCAP) with a small labeled subset of our internal TTS dataset for style model training. We take the softmax layer from the style classifier as style embedding and then apply this style embedding extraction model to generate soft style labels for our unlabelled internal TTS dataset. With this semi-supervised approach, reliable style embeddings are extracted to train a multi-style TTS system. As a result, we developed a controllable multi-style TTS system whose response matches the given target styles embedding, which could be extracted from the input query or manually assigned.

Includes members:
  Member "visualization and interpretation of latent spaces for controlling expressive speech synthesis through audio analysis":
    also connected through other hyperedges:
      (none)
  Member "challenging common assumptions in the unsupervised learning of disentangled representations":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "nestedvae isolating common factors via weak supervision")
  Member "multimodal speech emotion recognition using audio and text":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multimodal embeddings from language models")
  Member "towards end to end prosody transfer for expressive speech synthesis with tacotron":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "et gan cross language emotion transfer based on cycle consistent generative adversarial networks")
  Member "attention is all you need":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "using a thousand optimization tasks to learn hyperparameter search strategies")
  Member "uncovering latent style factors for expressive speech synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "towards end to end prosody transfer for expressive speech synthesis with tacotron")
  Member "wavenet a generative model for raw audio":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "noise estimation using density estimation for self supervised multimodal learning")
  Member "neural machine translation by jointly learning to align and translate":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "chameleon a deep learning meta architecture for news recommender systems phd thesis")

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.SD(Sound)