2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

ICASSP 2021 Paper Review Categories

* indicates that this line can be assigned as a paper's topic.

 
1:Audio and Acoustic Signal Processing
 1.1*:[AUD-MAAE] Modeling, Analysis and Synthesis of Acoustic Environments
 1.2*:[AUD-CLAS] Detection and Classification of Acoustic Scenes and Events
 1.3*:[AUD-AMHI] Auditory Modeling and Hearing Instruments
 1.4*:[AUD-ASAP] Acoustic Sensor Array Processing
 1.5*:[AUD-NEFR] Active Noise Control, Echo Reduction and Feedback Reduction
 1.6*:[AUD-SIRR] System Identification and Reverberation Reduction
 1.7*:[AUD-SEP] Audio and Speech Source Separation
 1.8*:[AUD-SEN] Signal Enhancement and Restoration
 1.9*:[AUD-QIM] Quality and Intelligibility Measures
 1.10*:[AUD-SARR] Spatial Audio Recording and Reproduction
 1.11*:[AUD-AMCT] Audio and Speech Modeling, Coding and Transmission
 1.12*:[AUD-MSP] Music Signal Analysis, Processing and Synthesis
 1.13*:[AUD-MIR] Music Information Retrieval and Music Language Processing
 1.14*:[AUD-AUMM] Audio for Multimedia and Audio Processing Systems
 1.15*:[AUD-BIO] Bioacoustics and Medical Acoustics
 1.16*:[AUD-SEC] Audio Security
 
2:Biomedical Imaging and Signal Processing
 2.1:[CIS-MI] Medical Imaging: Image formation, reconstruction, restoration
  2.1.1*:[CIF-IRR] Image reconstruction and restoration
  2.1.2*:[CIS-TIM] Tomographic imaging
  2.1.3*:[CIS-MRI] Magnetic resonance imaging
  2.1.4*:[CIS-AIM] Acoustic Imaging: Computational acoustic and ultrasound imaging
 2.2:[BIO-MIA] Medical image analysis
  2.2.1*:Detection and estimation
  2.2.2*:Registration and motion analysis
  2.2.3*:Feature extraction and fusion
 2.3*:[BIO-BI] Biological imaging
 2.4*:[BIO-BIA] Biological image analysis
 2.5:[BIO] Biomedical signal processing
  2.5.1*:Detection and estimation
  2.5.2*:Feature extraction and fusion
  2.5.3*:[BIO-PHY] Physiological signal processing (ECG, EEG, EMG)
 2.6*:[BIO-BCI] Brain/human-computer interfaces
 2.7*:[BIO-INFR] Bioinformatics
 
3:Computational Imaging
 3.1:[IMT] Computational Imaging Methods and Models
  3.1.1*:[IMT-CIS] Coded Image Sensing
  3.1.2*:[IMT-CST] Compressed Sensing
  3.1.3*:[IMT-SIM] Statistical Image Models
  3.1.4*:[IMT-SLM] Sparse and Low Rank Models
  3.1.5*:[IMT-GIM] Graphical Image Models
  3.1.6*:[IMT-LBM] Learning-Based Models
  3.1.7*:[IMT-PIM] Perceptual Image Models
 3.2:[CIF] Computational Image Formation
  3.2.1*:[CIF-SBR] Sparsity-Based Reconstruction
  3.2.2*:[CIF-SBI] Statistically-Based Inversion
  3.2.3*:[CIF-MIF] Multi-Image & Sensor Fusion
  3.2.4*:[CIF-OBI] Optimization-based Inversion Methods
  3.2.5*:[CIF-MLI] Machine Learning based Computational Image Formation
 3.3:[CIS] Computational Imaging Systems
  3.3.1*:[CIS-CPH] Computational Photography
  3.3.2*:[CIS-MIS] Mobile Imaging
  3.3.3*:[CIS-PIS] Pervasive Imaging
  3.3.4*:[CIS-HCC] Human Centric Computing
  3.3.5*:[CIS-CMI] Microscopic Imaging
  3.3.6*:[CIS-SSI] Spectral Sensing
  3.3.7*:[CIS-TIM] Tomographic Imaging
  3.3.8*:[CIS-MRI] Magnetic resonance imaging
  3.3.9*:[CIS-AIM] Acoustic Imaging: Computational acoustic and ultrasound imaging
  3.3.10*:[CIS-RIM] Radar Imaging
  3.3.11*:[CIS-NCI] Novel Computational Imaging Systems
  3.3.12*:[CIS-NLC] Non-Linear Computational Imaging Systems
 3.4*:[HSS] Computational Imaging Hardware and Software
  3.4.1:[HSS-HPC] High-performance embedded computing systems
  3.4.2:[HSS-BDC] Big Data Computational Imaging: High performance computing
  3.4.3:[HSS-HDD] Integrated Hardware/Digital Design
  3.4.4:[HSS-NSS] Non-traditional Sensor Systems
 
5:Image, Video, and Multidimensional Signal Processing
 5.1:[IVSMR] Image & Video Sensing, Modeling, and Representation
  5.1.1*:[SMR-SEN] Image & Video Sensing and Acquisition
  5.1.2*:[SMR-REP] Image & Video Representation
  5.1.3*:[SMR-HPM] Perception and Quality Models for Images & Video
  5.1.4*:[SMR-SSM] Statistical and Structural Image/Video Models
   5.1.4.1:[SMR-SSM-SMD] Statistical-Model Based Methods
   5.1.4.2:[SMR-SSM-STM] Structural-Model Based Methods
 5.2:[IVTEC] Image & Video Processing Techniques
  5.2.1*:[TEC-LNV] Linear, Nonlinear and Variational Processing
   5.2.1.1:[TEC-LNV-FIL] Linear and Nonlinear Filtering of Images & Video
   5.2.1.2:[TEC-LNV-PDE] Partial Differential Equation Based Processing of Images & Video
  5.2.2*:[TEC-MRS] Multiresolution Processing of Images & Video
  5.2.3*:[TEC-INV] Inverse Problems in Image and Video Processing
   5.2.3.1:[TEC-INV-RST] Restoration and Enhancement
   5.2.3.2:[TEC-INV-ISR] Interpolation, Super-Resolution, and Mosaicing
   5.2.3.3:[TEC-INV-FOR] Formation and Reconstruction
  5.2.4*:[TEC-BIP] Biomedical and biological image processing
  5.2.5*:[TEC-MLI] Machine Learning for Image Processing
 5.3:[IVCOM] Image & Video Communications
  5.3.1*:[COM-CDG] Image and Video Coding
   5.3.1.1:[COM-CDG-LOC] Lossy Coding of Images & Video
   5.3.1.2:[COM-CDG-LLC] Lossless Coding of Images & Video
   5.3.1.3:[COM-CDG-ERC] Error Resilience and Channel Coding for Image & Video Systems
  5.3.2*:[COM-NET] Imaging & Video Networks
  5.3.3*:[COM-WSE] Image & Video Processing for Watermarking and Security
  5.3.4*:[COM-MMC] Multimedia Communications
 5.4:[IVELI] Electronic Imaging
  5.4.1*:[ELI-SCN] Scanned Image Analysis and Processing
   5.4.1.1:ELI-SCN-SDP Image Scanning and Capture
   5.4.1.2:ELI-SCN-DOC Scanned Document Analysis, Processing, and Coding
  5.4.2*:[ELI-COL] Color and Multispectral Imaging
  5.4.3*:[ELI-PRT] Printing and Halftoning
  5.4.4*:[ELI-STE] Stereoscopic and Multiview Processing, Display And Coding
  5.4.5*:[ELI-HDW] Hardware and Software Systems for Image & Video Processing
  5.4.6*:[ELI-PCP] Point Cloud Processing
  5.4.7*:[ELI-AVR] Image and Video Processing Augmented and Virtual Reality
 5.5:[IVARS] Image & Video Analysis, Synthesis, and Retrieval
  5.5.1*:[ARS-ANL] Image and Video Analysis
   5.5.1.1:[ARS-ANL-RBS] Region, Boundary, Texture and Shape Analysis
   5.5.1.2:[ARS-ANL-IVA] Image & Video Mid Level Analysis
   5.5.1.3:[ARS-ANL-BIM] Image & Video Biometric Analysis
  5.5.2*:[ARS-IIU] Image & Video Interpretation and Understanding
  5.5.3*:[ARS-SRE] Image & Video Storage and Retrieval
  5.5.4*:[ARS-SRV] Image & Video Synthesis, Rendering, and Visualization
 
6:Information Forensics and Security
 6.1*:[ADP] Anonymization And Data Privacy
 6.2*:[APC] Applied Cryptography
 6.3*:[BIO] Biometrics
 6.4*:[CIT] Communication And Information Theoretic Security
 6.5*:[CYB] Cybersecurity
 6.6*:[MMF] Multimedia Forensics
 6.7*:[HWS] Hardware Security
 6.8*:[MMH] Multimedia Content Hash
 6.9*:[NET] Network Security
 6.10*:[SUR] Surveillance
 6.11*:[USH] Usability And Human Factors
 6.12*:[WAT] Watermarking And Data Hiding
 6.13*:[MMH-OTHS] Forensics & Security Related Applications
 
8:Machine Learning for Signal Processing
 8.1*:[MLR-APPL] Applications of machine learning
 8.2*:[MLR-COGP] Cognitive information processing
 8.3*:[MLR-DEEP] Deep learning techniques
 8.4*:[MLR-DICT] Dictionary learning
 8.5*:[MLR-GKM] Graphical and kernel methods
 8.6*:[MLR-MFC] Matrix factorizations/completion
 8.7*:[MLR-ICA] Independent component analysis
 8.8*:[MLR-INFO] Information-theoretic learning
 8.9*:[MLR-LEAR] Learning theory and algorithms
 8.10*:[MLR-LMM] Learning from multimodal data
 8.11*:[MLR-MUSAP] Applications in music and audio processing
 8.12*:[MLR-PRCL] Pattern recognition and classification
 8.13*:[MLR-PERF] Bounds on performance
 8.14*:[MLR-SBML] Subspace and manifold learning
 8.15*:[MLR-SLER] Sequential learning; sequential decision methods
 8.16*:[MLR-SSEP] Source separation
 8.17*:[MLR-TNSR] Tensor-based signal processing
 8.18*:[SMDSP-SAP] Sparsity-aware processing
 8.19*:[OTH-BGDT] Big Data
 8.20*:[MLR-DFED] Distributed/Federated learning
 8.21*:[MLR-REI] Reinforcement learning
 8.22*:[MLR-TRL] Transfer learning
 8.23*:[MLR-SSUP] Self-supervised and semi-supervised learning
 
9:Multimedia Signal Processing
 9.1:Signal Processing for Multimedia Applications
  9.1.1*:[ASLAS] Audio/Speech/Language Analysis and Synthesis
  9.1.2*:[CCMT] Compression, Coding, Media Conversion and Transcoding
  9.1.3*:[IVGAS] Image/Video/Graphics Analysis and Synthesis
  9.1.4*:[SYNA] Integration of Synthetic and Natural Audio/Video
  9.1.5*:[3DA] 3-D Audio Signal Processing
  9.1.6*:[3DV] 3-D Video Signal Processing
 9.2*:Technology Components and System Integration
 9.3:Human Centric Multimedia
  9.3.1*:[MHMI] Multimodal Human-machine Interfaces and Interaction
  9.3.2*:[MPIM] Multimodal Perception, Integration, and Multisensory Fusion
  9.3.3*:[QAUE] Subjective and Objective Quality Assessment, and User Experience
 9.4:Multimedia Environments
  9.4.1*:[AVEW] Audio-visual-haptic Environments and Workspaces
  9.4.2*:[MTAC] Multimodal Telepresence and Collaboration
  9.4.3*:[VAAR] Virtual and Augmented Reality
 9.5:Multimedia Databases and File Systems
  9.5.1*:[BIGM] Big Data Support for Multimedia
  9.5.2*:[KNOW] Knowledge and Semantics Modeling for Multimedia Databases
  9.5.3*:[SEAR] Multimedia Search and Retrieval
 9.6*:Multimedia Applications
 9.7*:Standards and Related Issues in Multimedia
 9.8:Multimedia Communications and Networking
  9.8.1*:[MCCC] Media Cloud Computing and Communication
  9.8.2*:[MSTRC] Multimedia Streaming, Transport, Error Resilience and Concealment
  9.8.3*:[SCNC] Distributed/Cooperative Networks and Communication
  9.8.4*:[WMMM] Wireless and Mobile Multimedia
 9.9:Emerging Areas in Multimedia
  9.9.1*:[DLMA] Deep Learning for Multimedia Analysis
  9.9.2*:[DLMP] Deep Learning for Multimedia Processing
 
10:Sensor Array and Multichannel Signal Processing
 10.1*:[SAM-APPL] Applications of sensor & array multichannel processing
 10.2*:[SAM-BEAM] Beamforming
 10.3*:[SAM-CALB] Array calibration
 10.4*:[SAM-CSSM] Compressed sensing and sparse modeling
 10.5*:[SAM-DOAE] Direction of arrival estimation and source localization
 10.6*:[SAM-GSSP] Geophysical and seismic signal processing
 10.7*:[SAM-IMGA] Inverse methods and imaging with array data
 10.8*:[SAM-LRNM] Learning models and methods for multi-sensor systems
 10.9*:[SAM-MCHI] Multichannel processing, identification, and modelling
 10.10*:[SAM-MAPR] Microphone array processing
 10.11*:[SAM-NWAV] Non-wave based array processing
 10.12*:[SAM-PERF] Performance analysis and bounds
 10.13*:[SAM-SDET] Source detection and separation
 10.14*:[SAM-SENS] Multi-sensor remote sensing of the environment
 10.15*:[SAM-STAP] Space-time adaptive methods
 10.16*:[SAM-TNSR] Tensor-based signal processing for multi-sensor systems
 10.17*:[SAM-MUCN] Multi-user and cooperative networks
 10.18*:[SAM-CAMS] Computational advances for multi-sensor systems
 10.19*:[RAS-DTCL] Target detection, classification, localization
 10.20*:[RAS-LCLZ] Source localization
 10.21*:[RAS-MIMO] MIMO Radar and waveform design
 10.22*:[RAS-SARI] Synthetic aperture radar/sonar and imaging
 10.23*:[RAS-SONR] Sonar and underwater signal processing
 10.24*:[RAS-TRCK] Target tracking
 10.25*:[BIO-SENS] Sensor arrays for medical signal and image processing
 10.26*:[SPC-MIMO] Multiple-input multiple-output communication systems
 10.27*:[SPC-MMIMO] Massive MIMO communication systems
 10.28*:[SSP-PARE] Parameter Estimation
 
11:Signal Processing for Communications and Networking
 11.1*:[SPC-MOD] Modulation, demodulation, encoding and decoding
  11.1.1:[SPC-MEPB] Modulation, encoding, pre-coding and beamforming
  11.1.2:[SPC-DETC] Detection, estimation, and demodulation
  11.1.3:[SPC-CMPR] Signal representation, coding and compression
 11.2*:[SPC-CHAN] Channel modelling and estimation
  11.2.1:[SPC-SYNC] Acquisition, synchronization and tracking
  11.2.2:[SPC-CHAN] Channel characterization, modelling, estimation and equalization
 11.3*:[SPC-MIMO] Multiple-Input Multiple-Output
  11.3.1:[SPC-MIMO] Multiple-input multiple-output communication systems
  11.3.2:[SPC-MMIMO] Massive MIMO communication systems
  11.3.3:[SPC-DMIMO] Distributed MIMO
 11.4*:[SPC-HIGH] High frequency and wideband communication
  11.4.1:[SPC-MMTH] Millimetre-wave and terahertz communications
  11.4.2:[SPC-UWBC] Ultra wideband communications
 11.5:[CNS-LLC] Low latency communications
 11.6:[SPC-INTF] Interference management techniques
 11.7*:[SPC-MULT] Multi-carrier and spread spectrum techniques
  11.7.1:[SPC-MULT] Multi-carrier, OFDM, and DMT communications
  11.7.2:[SPC-CDSS] CDMA and spread spectrum communications
  11.7.3:[SPC-DSLP] Digital subscriber loops and powerline communication
 11.8*:[SPCN-NETW] Networks and Network Resource allocation
  11.8.1:[SPC-RSRC] Scheduling and resource management
  11.8.2:[SPC-CROP] Cross-layer optimization
  11.8.3:[CNS-NSPRA] Optimal network signal processing and resource allocation
  11.8.4:[CNS-CLRD] Cross-Layer design
  11.8.5:[CNS-RSMG] Resource management issues
  11.8.6:[CNS-SQP] Scheduling and queuing protocols
 11.9*:[CNS-SENS] Sensor and ad-hoc networks
  11.9.1:[CNS-APPL] Applications of sensor networks
  11.9.2:[CNS-ADHC] Ad-hoc wireless networks
 11.10*:[SPC-COMP] Compensation and calibration of front end components
 11.11*:[SPCN-ENGY] Energy efficiency in communications
  11.11.1:[SPC-EAC] Energy Aware Communications
  11.11.2:[CNS-ENGY] Energy efficient sensor network algorithms
 11.12*:[SPCN-DIST] Distributed, adaptive, and collaborative communication techniques
  11.12.1:[SPC-SPCR] Signal processing for cognitive radios
  11.12.2:[CNS-SPDCN] Signal processing for distributed communications and networking
  11.12.3:[CNS-SPCN] Signal processing for cooperative networking
  11.12.4:[CNS-CCMCT] Cooperative and coordinated multi-cell techniques
  11.12.5:[CNS-DSCD] Distributed source and channel decoding
 11.13*:[SPC-ML] Machine Learning for Communications
 11.14*:[SPC-PERF] Information theory and performance bounds
  11.14.1:[SPC-INFO] Information-theoretic studies
  11.14.2:[SPC-PERF] Performance analysis and bounds
 11.15*:[SPC-SPARCO] Sparse SP techniques for communication
 11.16*:[SPC-APP] Applications involving of signal processing for communications
 11.17*:[CIT-PHYS] Physical Layer Security
  11.17.1:[SPC-PHYS] Physical layer security
  11.17.2:[CIT-COM-JAM] Jamming and anti-jamming techniques
  11.17.3:[CIT-COM-COV] Covert or stealthy communication via physical layers
  11.17.4:[CIT-COM-COOP] Security and trust in cooperative communications
  11.17.5:[CIT-COM-MIMO] Security and trust in MIMO and multiple-access techniques
  11.17.6:[CIT-COM-COG] Security in cognitive radio
  11.17.7:[CIT-PHY] Physical layer security
  11.17.8:[CIT-PHY-SKEY] Secret key extraction from channels
  11.17.9:[CIT-PHY-COD] Coding for physical layer security
  11.17.10:[CIT-PHY-MIMO] Physical layer security in MIMO systems
  11.17.11:[CIT-INF] Information theoretic security
  11.17.12:[CIT-INF-SECC] Security over channels
 
12:Signal Processing Theory and Methods
 12.1:[SMDSP] Sampling, Multirate Signal Processing and Digital Signal Processing
  12.1.1*:[SMDSP-SAM] Sampling Theory, Analysis and Methods
   12.1.1.1:[SMDSP-ALGO] Algorithm analysis
   12.1.1.2:[SMDSP-SAMP] Sampling, extrapolation, and interpolation
   12.1.1.3:[SMDSP-QUAN] Quantization effects
  12.1.2*:[SMDSP-CNS] Compressed and Nonuniform Sampling
   12.1.2.1:[SMDSP-CPSL] Compressive and nonuniform sampling
   12.1.2.2:[SMDSP-ASAL] Adaptive Sensing Algorithms
  12.1.3*:[SMDSP-RECO] Algorithms for signal filtering, restoration, enhancement, and reconstruction
  12.1.4*:[SMDSP-MRA] Multiresolution Analysis, filter banks, and wavelets
   12.1.4.1:[SMDSP-APPL] Applications of digital and multirate signal processing
   12.1.4.2:[SMDSP-BANK] Filter bank design and theory
   12.1.4.3:[SMDSP-MULT] Multirate processing and multiresolution methods
   12.1.4.4:[SMDSP-TFSR] Time-frequency analysis and signal representation
  12.1.5*:[SMDSP-FAT] Fast Algorithms and Transforms
   12.1.5.1:[SMDSP-FAST] Fast algorithms for digital signal processing
   12.1.5.2:[SMDSP-TRSF] Transforms for signal processing
  12.1.6*:[SMDSP-SAP] Sparsity-aware processing
 12.2:[SIPG] Signal and Information Processing over Graphs
  12.2.1*:[SIPG-SA] Statistical Approaches (models, etc.)
   12.2.1.1:[NEG-INFO] Information-theoretic studies
   12.2.1.2:[SPIG-STOC] Stochastic processes over graphs (T-SIPN & TSP)
   12.2.1.3:[SIPG-MEND] Modeling and estimation of network dynamics (T-SIPN)
   12.2.1.4:[SIPG-MNE] Modeling of network evolution (T-SIPN)
  12.2.2*:[SIPG-DA] Deterministic Approaches (graph filtering, graph transforms, etc.)
   12.2.2.1:[NEG-SPGR] Signal processing over graphs (filtering, transforms, etc)
   12.2.2.2:[NEG-SAMP] Sampling over graphs
   12.2.2.3:[SIPG-DIS] Distributed processing of graph data (T-SIPN)
  12.2.3*:[SIPG-GRA] Graph Representations and Analysis
   12.2.3.1:[NEG-GRAN] Graph analysis for signal processing
   12.2.3.2:[NEG-SPGT] Spectral graph theory and algebraic topology algorithms
   12.2.3.3:[NEG-SYLO] System level optimization
  12.2.4*:[SIPG-AL] Adaptation and Learning Over Graphs
   12.2.4.1:[NEG-ADLE] Adaptation and learning over graphs
   12.2.4.2:[NEG-ASAL] Adaptive sensing algorithms
 12.3:[OPT] Optimization Methods for Signal Processing
  12.3.1*:[OPT-CVXR] Convex optimization and relaxation for SP
  12.3.2*:[OPT-DOPT] Distributed optimization for SP
  12.3.3*:[OPT-NCVX] Non-convex methods for SP
  12.3.4*:[OPT-SPARSE] Sparse optimization techniques for SP
 12.4*:[OTH-QUAN] Quantum signal processing
 12.5*:[ASP] Adaptive Signal Processing
  12.5.1:[ASP-ANAL] Adaptive filter analysis and design
  12.5.2:[ASP-APPL] Applications of adaptive filters
  12.5.3:[ASP-FAST] Fast algorithms for adaptive filtering
  12.5.4:[ASP-FREQ] Frequency-domain and subband adaptive filtering
 12.6:[SSP] Statistical Signal Processing
  12.6.1*:[SSP-DTM] Detection Theory and Methods
   12.6.1.1:[SSP-DETC] Detection
   12.6.1.2:[SSP-RDET] Robust detection, estimation, and tracking
  12.6.2*:[SSP-ETM] Estimation Theory and Methods
   12.6.2.1:[SSP-PARE] Parameter estimation
   12.6.2.2:[SSP-IDEN] System identification
   12.6.2.3:[SSP-SPEC] Spectral analysis and spectral estimation
  12.6.3*:[SSP-CLAS] Classification methods
  12.6.4*:[SSP-ANA] Analysis
   12.6.4.1:[SSP-PERF] Performance analysis and bounds
   12.6.4.2:[SSP-SSAN] Statistical signal analysis
  12.6.5*:[SSP-LNSP] Linear and Nonlinear Systems and Signal Processing
   12.6.5.1:[SSP-DECO] Deconvolution
   12.6.5.2:[SSP-FILT] Filtering
   12.6.5.3:[SSP-SSEP] Signal separation
   12.6.5.4:[SSP-REST] Signal restoration
   12.6.5.5:[SSP-NSSP] Nonstationary statistical signal processing
   12.6.5.6:[SSP-NGAU] Non-Gaussian signals and noise
  12.6.6*:[SSP-BSP] Bayesian signal processing
  12.6.7*:[SSP-MM] Models and Methods
   12.6.7.1:[SSP-HIER] Hierarchical models & tree structured signal processing
   12.6.7.2:[SSP-HOSM] Higher-order statistical methods
   12.6.7.3:[SSP-NPAR] Non-parametric methods
   12.6.7.4:[SSP-SNMD] Signal and noise modeling
   12.6.7.5:[SSP-SYSM] System modeling
   12.6.7.6:[SSP-SPRS] SP methods for structured low dimensional models
  12.6.8*:[SSP-TRAC] Tracking algorithms
  12.6.9*:[SSP-APPL] Applications of statistical signal processing techniques
 12.7:Signal Processing over Networks
  12.7.1*:[DPON] Distributed Processing and Optimization over Networks
   12.7.1.1:[NEG-ADHC] Ad-hoc wireless networks
   12.7.1.2:[NEG-CLRD] Cross-layer design
   12.7.1.3:[ADEL-DAN] Distributed adaptation over networks
   12.7.1.4:[NEG-RSMG] Resource management issues
   12.7.1.5:[NEG-ENGY] Energy efficient sensor network algorithms
   12.7.1.6:[NEG-FUSE] Data fusion from multiple sensors
   12.7.1.7:[ADEL-CNS] Consensus over network systems
   12.7.1.8:[ADEL-ONS] Optimization over network systems
  12.7.2*:[EDLN] Estimation, Detection and Learning over Networks
   12.7.2.1:[NEG-LOCL] Source localization in sensor networks
   12.7.2.2:[NEG-LRNM] Learning models and methods
   12.7.2.3:[ADEL-DDE] Distributed detection and estimation
   12.7.2.4:[ADEL-DLN] Distributed learning over networks
   12.7.2.5:[ADEL-SLN] Sequential learning over networks
   12.7.2.6:[ADEL-DMN] Decision making over networks
  12.7.3*:[NEG-APPL] Applications of sensor networks
 12.8:[SMDSP-SAP] Sparsity-aware Processing
  12.8.1*:Sparse/low-dimensional signal recovery, parameter estimation and regression
  12.8.2*:Structured matrix factorization, low-rank models, matrix completion
  12.8.3*:Dictionary learning; subspace and manifold learning
 
13:Speech Processing
 13.1*:[SPE-SPRD] Speech Production
 13.2*:[SPE-SPER] Speech Perception and Psychoacoustics
 13.3:[SPE-ANLS] Speech Analysis
  13.3.1*:Signal, intonation, and paralinguistics modeling
  13.3.2*:Emotion
  13.3.3*:Language Disorders
 13.4:[SPE-SYNT] Speech Synthesis and Generation
  13.4.1*:Voice Conversion
  13.4.2*:Machine learning for speech synthesis, including end-to-end methods
  13.4.3*:General Topics in Speech Synthesis
 13.5*:[SPE-CODI] Speech Coding
 13.6:[SPE-ENHA] Speech Enhancement and Separation
  13.6.1*:Speech Enhancement Methods, including Deep Learning Methods
  13.6.2*:Speech Separation and Denoising
  13.6.3*:Multichannel Methods for Speech Enhancement/Separation (e.g., Beamforming)
 13.7*:[SPE-RECO] Acoustic Modeling for Automatic Speech Recognition
 13.8*:[SPE-ROBU] Robust Speech Recognition
 13.9*:[SPE-ADAP] Speech Adaptation/Normalization
 13.10:[SPE-LVCR] Large Vocabulary Continuous Recognition/Search
  13.10.1*:End-to-end approaches
  13.10.2*:Other LVSCR approaches
 13.11*:[SPE-MULT] Multilingual Recognition and Identification
 13.12:[SPE-GASR] General Topics in Speech Recognition
  13.12.1*:Hardware/network-aware methods
  13.12.2*:Word spotting
  13.12.3*:Metadata (e.g., emotion, speaker, accent) extraction from acoustics
  13.12.4*:New algorithms and approaches
  13.12.5*:Corpora, annotation, and other resources
  13.12.6*:Lexical Modeling and Access
  13.12.7*:Resource Constrained Speech Recognition
  13.12.8*:Other topics in speech recognition
 13.13:[SPE-SPKR] Speaker Recognition and Characterization
  13.13.1*:Speaker verification and anti-spoofing
  13.13.2*:Speaker recognition/identification
  13.13.3*:Speaker diarization
 13.15*:[SPE-VAD] Voice Activity Detection and End-pointing
 
14:Human Language Technology
 14.1*:[HLT-LANG] Language Modeling
 14.2*:[HLT-MTSW] Machine Translation for Spoken and Written Language
 14.3*:[HLT-UNDE] Spoken Language Understanding and Computational Semantics
 14.4*:[HLT-DIAL] Discourse and Dialog
 14.5*:[HLT-SDTM] Spoken Document Retrieval and Text Mining
 14.6*:[HLT-STPA] Segmentation, Tagging, and Parsing
 14.7*:[HLT-LACL] Language Acquisition and Learning
 14.8*:[HLT-MLMD] Machine Learning Methods for Language
 14.9*:[HLT-LRES] Language Resources and Systems
 14.10*:[HLT-MMPL] Multimodal Processing of Language
 
15:Applied Signal Processing Systems
 15.1:Signal Processing Hardware [DIS-PROG, DIS-MLTC, DIS-SOCP]
  15.1.1*:VLSI Circuits & Systems
  15.1.2*:FPGA and Programmable Logic
  15.1.3*:Application-Specific Processors
  15.1.4*:Emerging architectures
 15.2*:Signal Processing Software [DIS-LPWR, DIS-MLTC, DIS-SOCP]
 15.3:Design & Synthesis [DIS-ARCH, DIS-LPWR]
  15.3.1*:Algorithm and architecture co-optimization
  15.3.2*:Modelling and model-based design
  15.3.3*:Compilers, synthesis tools and design automation
 15.4:Signal Processing over IoT [OTH-IoT]
  15.4.1*:Sensor Networks
  15.4.2*:Autonomous and Cyber-Physical Systems
 15.5:Emerging Topics [OTH-EMRG]
  15.5.1*:Smart Devices and Wearables
  15.5.2*:Biomedical and biosystems
  15.5.3*:Terahertz Technology and Mixed Signal Processing
 15.6:Signal Processing Systems [DIS-EMSA]
  15.6.1*:Embedded Systems
  15.6.2*:Communications and Networking
  15.6.3*:Blockchain, Memory and Storage
  15.6.4*:Image, video and audio
  15.6.5*:Sensing and sensor processing
  15.6.6*:Security
  15.6.7*:Data science and machine learning
  15.6.8*:Autonomous systems, VR/AR, robotics
 
16:[OTH-EDU] Education
 16.1*:Education
 
18:5-Minute Video Clip Contest (5-MICC)
 18.1*:5-MICC