human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "voice recognition algorithms using mel frequency cepstral coefficient mfcc and dynamic time warping dtw techniques"
  Abstract: Abstract — Digital processing of speech signal and voice recognition algorithm is very important for fast and accurate automatic voice recognition technology. The voice is a signal of infinite information. A direct analysis and synthesizing the complex voice signal is due to too much information contained in the signal. Therefore the digital signal processes such as Feature Extraction and Feature Matching are introduced to represent the voice signal. Several methods such as Liner Predictive Predictive Coding (LPC), Hidden Markov Model (HMM), Artificial Neural Network (ANN) and etc are evaluated with a view to identify a straight forward and effective method for voice signal. The extraction and matching process is implemented right after the Pre Processing or filtering signal is performed. The non-parametric method for modelling the human auditory perception system, Mel Frequency Cepstral Coefficients (MFCCs) are utilize as extraction techniques. The non linear sequence alignment known as Dynamic Time Warping (DTW) introduced by Sakoe Chiba has been used as features matching techniques. Since it’s obvious that the voice signal tends to have different temporal rate, the alignment is important to produce the better performance.This paper present the viability of MFCC to extract features and DTW to compare the test patterns.

Connected through hyperedge HE-1 (induced by source paper "short range audio channels security survey of mechanisms applications and research challenges"):
  with members:
    - "perils of zero interaction security in the internet of things"
    - "a survey on context based co presence detection techniques"
    - "doubleecho mitigating context manipulation attacks in copresence verification"
    - "survey and systematization of secure device pairing"
    - "continuous authentication for voice assistants"
    - "dolphinattack inaudible voice commands"
    - "a survey on homomorphic encryption schemes theory and implementation"
    - "don t skype type acoustic eavesdropping in voice over ip"

Connected through hyperedge HE-2 (induced by source paper "jointly aligning and predicting continuous emotion annotations"):
  with members:
    - "trainable time warping aligning time series in the continuous time domain"
    - "the priori emotion dataset linking mood to emotion detected in the wild"
    - "capturing long term temporal dependencies with convolutional networks for continuous emotion recognition"
    - "progressive neural networks for transfer learning in emotion recognition"
    - "end to end multimodal emotion recognition using deep neural networks"
    - "learning representations of emotional speech with deep convolutional generative adversarial networks"
    - "emotion recognition by body movement representation on the manifold of symmetric positive definite matrices"
    - "avec 2016 depression mood and emotion recognition workshop and challenge"

Connected through hyperedge HE-3 (induced by source paper "dynamic time warping in strongly subquadratic time algorithms for the low distance regime and approximate evaluation"):
  with members:
    - "the one way communication complexity of dynamic time warping distance"
    - "approximating edit distance within constant factor in truly sub quadratic time"
    - "on estimating edit distance alignment dimension reduction and embeddings"
    - "locality sensitive hashing of curves"
    - "products of euclidean metrics and applications to proximity questions among curves"
    - "streaming algorithms for computing edit distance without exploiting suffix trees"
    - "dynamic time warping and geometric edit distance breaking the quadratic barrier"
    - "quadratic conditional lower bounds for string problems and dynamic time warping"

Connected through hyperedge HE-4 (induced by source paper "cross modal variational auto encoder with distributed latent spaces and associators"):
  with members:
    - "variational autoencoded regression high dimensional regression of visual data on complex manifold"
    - "learning to localize sound source in visual scenes"
    - "mix and match networks encoder decoder alignment for zero pair image translation"
    - "speech commands a dataset for limited vocabulary speech recognition"
    - "cross modal deep variational hand pose estimation"
    - "multimodal generative models for scalable weakly supervised learning"
    - "crossing nets combining gans and vaes with a shared latent space for hand pose estimation"
    - "conditional generation of multi modal data using constrained embedding space mapping"

Connected through hyperedge HE-5 (induced by source paper "an attention based speaker naming method for online adaptation in non fixed scenarios"):
  with members:
    - "cosface large margin cosine loss for deep face recognition"
    - "arcface additive angular margin loss for deep face recognition"
    - "voxceleb2 deep speaker recognition"
    - "sphereface deep hypersphere embedding for face recognition"
    - "attention is all you need"
    - "learning without forgetting"
    - "joint face detection and alignment using multitask cascaded convolutional networks"
    - "deep multimodal speaker naming"

Connected through hyperedge HE-6 (induced by source paper "effective and general evaluation for instruction conditioned navigation using dynamic time warping"):
  with members:
    - "from language to goals inverse reinforcement learning for vision based instruction following"
    - "stay on the path instruction fidelity in vision and language navigation"
    - "the streetlearn environment and dataset"
    - "touchdown natural language navigation and spatial reasoning in visual street environments"
    - "on evaluation of embodied navigation agents"
    - "mapping instructions to actions in 3d environments with visual goal prediction"
    - "mapping navigation instructions to continuous control actions with position visitation prediction"
    - "matterport3d learning from rgb d data in indoor environments"

Connected through hyperedge HE-7 (induced by source paper "general evaluation for instruction conditioned navigation using dynamic time warping"):
  with members:
    - "rerere remote embodied referring expressions in real indoor environments"
    - "stay on the path instruction fidelity in vision and language navigation"
    - "the streetlearn environment and dataset"
    - "touchdown natural language navigation and spatial reasoning in visual street environments"
    - "on evaluation of embodied navigation agents"
    - "mapping instructions to actions in 3d environments with visual goal prediction"
    - "mapping navigation instructions to continuous control actions with position visitation prediction"
    - "vision and language navigation interpreting visually grounded navigation instructions in real environments"

Connected through hyperedge HE-8 (induced by source paper "the one way communication complexity of dynamic time warping distance"):
  with members:
    - "locality sensitive hashing of curves"
    - "products of euclidean metrics and applications to proximity questions among curves"
    - "edit distance sketching streaming and document exchange"
    - "dynamic time warping and geometric edit distance breaking the quadratic barrier"
    - "efficient deterministic single round document exchange for edit distance"
    - "quadratic conditional lower bounds for string problems and dynamic time warping"
    - "approximating dynamic time warping and edit distance for a pair of point sequences"
    - "sparsedtw a novel approach to speed up dynamic time warping"

Question: Please tell me which class the center node 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.MM(Multimedia)