ICASSP 2017 Paper Review Categories

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

1:Audio and Acoustic Signal Processing
 1.1*:Modeling, Analysis and Synthesis of Acoustic Environments
 1.2*:Auditory Modeling and Hearing Aids
 1.3:Acoustic Sensor Array Processing
  1.3.1*:Source Localization and Array Calibration
  1.3.2*:Microphone Array Design and Beamforming Methods
  1.3.3*:Multi-microphone Speech Enhancement
  1.3.4*:Sound-Field Analysis and Loudspeaker Array Processing
 1.4*:Active Noise Control, Echo Reduction and Feedback Reduction
 1.5*:System Identification and Reverberation Reduction
 1.6:Audio and Speech Source Separation
  1.6.1*:Multichannel Separation
  1.6.2*:NMF-based Separation
  1.6.3*:Deep Learning-based Separation
 1.7*:Signal Enhancement and Restoration
 1.8*:Quality and Intelligibility Measures
 1.9*:Spatial Audio Recording and Reproduction
 1.10*:Audio and Speech Modeling, Coding and Transmission
 1.11:Music Signal Analysis, Processing and Synthesis
  1.11.1*:Models and Representation for Music Signals
  1.11.2*:Pitch and Multi-pitch Estimation
  1.11.3*:Content-based Audio Analysis and Classification
  1.11.4*:Source Separation of Music Signals
 1.12:Music Information Retrieval and Music Language Processing
  1.12.1*:Transcription and Segmentation
  1.12.2*:Melody, Note, Chord, Key, and Rhythm Estimation and Detection
  1.12.3*:Similarity, Emotion and Retrieval
  1.12.4*:Symbolic Music Processing and Score Following
 1.13*:Audio for Multimedia
 1.14*:Audio Processing Systems and Transducers
 1.15*:Bioacoustics and Medical Acoustics
2:Bio Imaging and Signal Processing
 2.1:Medical imaging
  2.1.1*:Image formation
  2.1.2*:Reconstruction and restoration
  2.1.3*:Computed tomography (CT, PET or SPECT)
  2.1.4*:Biomedical Imaging
  2.1.5*:Magnetic resonance imaging
  2.1.6*:Ultrasound imaging
 2.2:Medical image analysis
  2.2.3*:Feature extraction and classification
 2.3:Bioimaging and microscopy
  2.3.1*:Cellular and molecular imaging
  2.3.2*:Deconvolution and inverse problems
  2.3.3*:Segmentation and analysis
  2.3.4*:Tracking and motion analysis
 2.4:Biomedical signal processing
  2.4.1*:Physiological signals (ECG, EEG, ...)
  2.4.2*:Detection and estimation
  2.4.3*:Feature extraction and classification
  2.4.4*:Multi-channel processing
  2.5.1*:Genomics and proteomics
  2.5.2*:Computational biology and biological networks
3:Design and Implementation of Signal Processing Systems
 3.1*:Algorithm and architecture co-optimization
 3.2*:Compilers and tools for DSP implementation
 3.3*:DSP algorithm implementation in hardware and software
 3.4*:Low-power signal processing techniques and architectures
 3.5*:Programmable and reconfigurable DSP architectures
 3.6*:System-on-chip architectures for signal processing
4:Image, Video, and Multidimensional Signal Processing
 4.1:Image/Video Coding
  4.1.1*:Still Image Coding
  4.1.2*:Video Coding
  4.1.3*:Stereoscopic and 3-D Coding
  4.1.4*:Distributed Source Coding
  4.1.5*:Image/Video Transmission
 4.2:Image/Video Processing
  4.2.1*:Image Filtering
  4.2.4*:Image Segmentation
  4.2.5*:Video Segmentation and Tracking
  4.2.6*:Morphological Processing
  4.2.7*:Stereoscopic and 3-D Processing
  4.2.8*:Image Feature Extraction
  4.2.9a*:Image Analysis
  4.2.9b*:Image Analysis
  4.2.10*:Video Feature Extraction
  4.2.11*:Video Analysis
  4.2.14*:Interpolation and Super-resolution
  4.2.15*:Motion Detection and Estimation
 4.3:Image Formation
  4.3.1*:Remote Sensing Imaging
  4.3.2*:Geophysical and Seismic Imaging
  4.3.3*:Optical Imaging
  4.3.4*:Synthetic-Natural Hybrid Image Systems
 4.4:Image Scanning, Display, and Printing
  4.4.1*:Scanning and Sampling
  4.4.2*:Quantization and Halftoning
  4.4.3*:Color Reproduction
  4.4.4*:Image Representation and Rendering
  4.4.5*:Display and Printing Systems
  4.4.6*:Image Quality Assessment
 4.5:Image/Video Storage, Retrieval
  4.5.1*:Image and Video Databases
  4.5.2*:Image Indexing and Retrieval
  4.5.3*:Video Indexing, Retrieval and Editing
5:Information Forensics and Security
 5.1:Watermarking and Steganography
  5.1.1*:Content transforms
  5.1.2*:Theoretical watermarking models
  5.1.3*:Watermark embedding/detection algorithms
  5.1.4*:Perceptual modeling and watermark shaping
  5.1.5*:Watermark resynchronization techniques
  5.1.6*:Watermark benchmarking and security analysis
 5.2:Passive Forensic Analysis
  5.2.1*:Sensor and channel forensics
  5.2.2*:Signal processing forensics
  5.2.3*:Behavior and social interactions forensics
  5.2.4*:Communications forensics
  5.2.5*:Anti-forensics and countermeasures
  5.2.6*:Fusion and cross-references
  5.2.8*:Forensic protocols
  5.3.1*:Biometric sensor design
  5.3.2*:Feature extraction algorithms
  5.3.3*:Feature matching and fusion techniques
  5.3.4*:Biometric security and privacy
  5.3.5*:Databases and performance evaluation
 5.4:Multimedia Content Hash
  5.4.1*:Global content hash functions
  5.4.2*:Local features detectors
  5.4.3*:Local features descriptors
  5.4.4*:Nearest neighbor search algorithms
  5.4.5*:Benchmarking and reference datasets
  5.4.6*:Security analysis
 5.5:Communications and Physical Layer Security
  5.5.1*:Jamming and anti-jamming
  5.5.2*:Covert or stealthy communication
  5.5.3*:Secret key extraction from channels
  5.5.4*:Security and trust in communications
  5.5.5*:Threats and attacks analysis
 5.6:Information Theoretic Security
  5.6.1*:Security over channels: wire-tap, broadcast, multiple access, etc
  5.6.2*:Data security and cryptography
  5.6.3*:Secret key generation, sharing, distribution
  5.6.4*:Privacy and trust
  5.6.5*:Shannon theory
 5.7:Signal Processing and Cryptography
  5.7.1*:Multimedia encryption
  5.7.2*:Signal processing in the encrypted domain
  5.7.3*:Traitor tracing codes
  5.7.4*:Visual secret sharing
  5.7.5*:Side channel attacks
 5.8:Video- and Signal-based Surveillance
  5.8.1*:Sensor-centric processing
  5.8.2*:Processing, detection, tracking & recognition
  5.8.3*:Visualization and interaction concepts for surveillance systems
  5.8.4*:Analytics, situation awareness and decision making
  5.8.5*:Security and privacy
 5.9:Security-related applications
  5.9.1*:Surveillance and intelligence gathering
  5.9.2*:Access control systems
  5.9.3*:Content protection, identification and monitoring
  5.9.4*:Content authentication and tamper detection
  5.9.5*:Cloud and distributed computing systems
  5.9.6*:Smart grid and power/energy systems
  5.9.7*:Social media and network systems
  5.9.8*:Privacy enhancing technologies
  5.9.9*:Crime scene analysis
  5.9.10*:Signal processing for secure documents
6:Industry DSP Technology
 6.1:Emerging Signal Processing Applications
  6.1.1*:M2M Technology
  6.1.2*:Display , Cameras and 3D Technology
  6.1.3*:Applications of Social Signal Processing
  6.1.4*:Green Technologies for Signal Processing
  6.1.5*:DSP for Smart Devices
  6.1.6*:Signal Processing Technology for Cloud Services
  6.1.7*:Signal Processing for Mobile and Embedded Application
  6.1.8*:Business intelligence and Big Data Applications
  6.1.9*:Digital and Software RF Processing
  6.1.10*:Terahertz Technology and Signal Processing
 6.2:DSP Tools and Rapid Prototyping
  6.2.1*:DSP Simulation Tools
  6.2.2*:Rapid Prototyping and languages
  6.2.3*:DSP Libraries
  6.2.4*:Operating Systems
 6.3:Communication Technologies
  6.3.1*:Cellular and Satellite Telephony
  6.3.2*:Data Communications and Networking
  6.3.3*:Sortware-Defined Radios
 6.4*:Speech Processing Applications
  6.4.1*:Speaker Recognition
  6.4.2*:Speech Compression
  6.4.3*:Speech Enhancement
  6.4.4*:Speech Recognition
  6.4.5*:Speech Synthesis
 6.5:Multimedia and DTV Technologies
  6.5.1*:DSP Implementations of Music, Speech, and Audio
  6.5.2*:Image and Video Applications
  6.5.3*:Standards and Format Conversions
  6.5.4*:Internet and Teleconferencing
 6.6:Adaptive Interference Cancellation
  6.6.1*:Smart Antennas
  6.6.2*:Active Sound Reduction
  6.6.3*:Acoustic and Electrical Noise and Echo Cancellation
  6.6.4*:Hands-Free Telephony
 6.7:Automotive Applications
  6.7.1*:Intelligent Dashboards, Vehicles, and Highways (IVHS)
  6.7.2*:Engine Management
  6.7.3*:Route Planning and Tracking
  6.7.4*:New Consumer Applications
  6.7.5*:Power Systems and Motor Controls
 6.8:Defense and Security Applications
  6.8.1*:Optical Correlation
  6.8.2*:Decluttering Target Identification and Tracking
  6.8.3*:DSP-Based Cryptography, Stenography, and Watermarking
  6.8.4*:Radar and Sonar
 6.9:DSP Chips and Architectures
  6.9.1*:Mixed Signal Processing
  6.9.2*:Special-Purpose and FPGA DSPs
  6.9.3*:Host-Based Signal Processing
  6.9.4*:Multiprocessor Architectures
 6.10:Other ITT Topics
  6.10.3*:Other Sub-Topics
7:Machine Learning for Signal Processing
 7.1*:Learning Theory and Modeling
 7.2*:Bayesian Learning and Modeling
 7.3*:Sequential learning; sequential decision methods
 7.4*:Information-theoretic learning
 7.5*:Neural network learning
 7.6*:Graphical and kernel models
 7.7*:Bounds on performance
 7.8*:Blind Signal Separation and Independent Component Analysis
 7.9*:Signal detection, Pattern Recognition and Classification
 7.10*:Bioinformatics Applications
 7.11*:Biomedical Applications and Neural Engineering
 7.12*:Intelligent Multimedia and Web Processing
 7.13*:Communications Applications
 7.14*:Speech and Audio Processing Applications
 7.15*:Image and Video Processing Applications
 7.16*:Tensor and Structured Matrix Methods
 7.17*:Machine Learning from Big Data
 7.18*:Scalable Learning Algorithms
 7.19*:Other Applications
8:Multimedia Signal Processing
 8.1:Multimodal signal processing
  8.1.1*:Joint processing/presentation of audio-visual and multimodal information
  8.1.2*:Fusion/fission of sensor information or multimodal data
  8.1.3*:Integration of media, art, and multimedia technology
  8.1.4*:Analysis and feature extraction of multimodal data
 8.2:Virtual reality and 3D imaging
  8.2.1*:2D and 3D graphics/geometry coding and animation
  8.2.2*:3D audio and video processing
  8.2.3*:Point cloud processing
  8.2.4*:Virtual reality and mixed-reality in networked environments
 8.3:Big data and learning-based media processing
  8.3.1*:Big data and cloud media processing
  8.3.2*:Traditional learning-based media processing
  8.3.3*:Deep learning-based media processing
  8.3.4*:Multimedia data mining
 8.4:Graph signal processing for multimedia
  8.4.1*:Graph-based audio, image and video processing
  8.4.2*:Prediction and learning in graphs for multimedia
  8.4.3*:Applications for graph signal processing
 8.5:Multimedia communications and networking
  8.5.1*:Wireless and mobile multimedia communication
  8.5.2*:Media streaming, media content distribution, and storage
  8.5.3*:Quality of service provisioning
  8.5.4*:Cross-layer design for multimedia communication
  8.5.5*:Overlay, peer-to-peer, and peer-assisted networking for multimedia
  8.5.6*:Home networking for multimedia
  8.5.7*:Location-aware multimedia computing
  8.5.8*:Multimedia sensor and ad hoc networks
  8.5.9*:Media compression and related standardization activities
  8.5.10*:Distributed source and source-channel coding
  8.5.11*:Social network and media sharing
 8.6:Multimedia human-machine interface and interaction
  8.6.1*:Human perception modelling
  8.6.2*:Modeling of multimodal perception
  8.6.3*:Human-human and human-computer dialog
  8.6.4*:Multimodal interfaces
  8.6.5*:Brain-computer interfaces
 8.7:Quality Assessment
  8.7.1*:Subjective visual quality assessment
  8.7.2*:Objective visual quality assessment
  8.7.3*:Subjective auditory quality assessment
  8.7.4*:Objective auditory quality assessment
  8.7.5*:Evaluation of user experience, cross-modal assessment
  8.7.6*:Standardization activities
 8.8:Multimedia databases and digital libraries
  8.8.1*:Visual indexing, analysis and representation
  8.8.2*:Audio indexing, analysis and representation
  8.8.3*:Content-based and context-based information retrieval
  8.8.4*:Knowledge and semantics in media annotation and retrieval
  8.8.5*:Fingerprinting and duplicate detection
 8.9:Multimedia computing systems and applications
  8.9.1*:Multimedia system design
  8.9.2*:Distributed multimedia systems
  8.9.3*:Entertainment and gaming
  8.9.4*:e-Health and telemedicine
  8.9.5*:IP video/web conferencing
 8.10:Hardware and software for multimedia systems
  8.10.1*:Multimedia hardware design
  8.10.2*:Real-time multimedia systems
  8.10.3*:Implementations on graphics processing units (GPUs)
  8.10.4*:Implementations on general-purpose processors, multimedia processors, DSPs, multi-core processors
  8.10.5*:Implementations in portable/wearable systems
  8.10.6*:Power-aware systems for multimedia
 8.11:Haptic technology and interaction
  8.11.1*:Processing and rendering of haptic signals
  8.11.2*:Compression and transmission of haptic signals
  8.11.3*:Audio-visual-haptic environments
  8.11.4*:Multimedia applications using haptics
 8.12:Perceptual and bio-inspired multimedia systems and signal processing
  8.12.1*:Perceptual bio-inspired signal processing for multimedia
  8.12.2*:Multimodal signal fusion in humans and animals
  8.12.3*:Joint perceptual, bio-inspired and conventional multimedia signal processing
 8.13:Other multimedia applications
  8.13.1*:Multimedia authoring and composition
  8.13.3*:Multimedia applications using Crowdsourcing
  8.13.4*:Multimedia signal processing for robotics and automation
  8.13.5*:Social, mobile, and Internet of things media Processing
9:Sensor Array and Multichannel Signal Processing
 9.1:Sensor Array Processing
  9.1.2*:Physics-based sensor array processing
  9.1.3*:Inverse methods
  9.1.4*:Array calibration methods
  9.1.5*:Synthetic aperture methods
  9.1.6*:Signal detection and parameter estimation
  9.1.7*:Direction-of-arrival estimation
  9.1.8*:Source localization, classification, and tracking
  9.1.9*:Source separation and channel identification
 9.2:Adaptive Array Signal Processing
  9.2.1*:Adaptive beamforming
  9.2.2*:Space-time adaptive processing
  9.2.3*:MIMO radar and waveform diversity
  9.2.4*:Computational advances in array processing
 9.3:Multi-channel Signal Processing
  9.3.1*:Channel modeling and equalization
  9.3.2*:Multi-channel transceiver design
  9.3.3*:Sparsity structures in multichannel signal processing
  9.3.4*:Multi-channel processing with non-wave based sensors
  9.3.5*:Tensor-based signal processing for multi-sensor systems
 9.4:Multi-antenna and Multi-channel Signal Processing for Communications
  9.4.1*:MIMO systems and algorithms
  9.4.2*:Space-time coding and decoding algorithms
  9.4.3*:MIMO space-time code design and analysis
  9.4.4*:Multi-user MIMO networks
  9.4.5*:Array processing for wireless communications
  9.4.6*:Multi-antenna/multi-channel processing for cognitive radios
  9.4.7*:Massive MIMO array processing
 9.5:Sensor and Relay Networks
  9.5.1*:Sensor and relay network signal processing
  9.5.2*:Network beamforming and coding
  9.5.3*:Distributed processing and optimization, cooperative algorithms
  9.5.4*:Data fusion and decision fusion from multiple sensor types
  9.5.5*:Multi-Sensor processing for smart grid and energy systems
  9.5.6*:Network agent activity monitoring
  9.5.7*:Wireless acoustic sensor networks
 9.6:Applications of Sensor Array and Multi-channel Signal Processing
  9.6.1*:Radar array processing
  9.6.2*:Sonar array processing
  9.6.3*:Microphone array processing
  9.6.4*:Hyperspectral processing and unmixing
  9.6.5*:Integrated multi-model sensing
  9.6.6*:Super-resolution sensing and reconstruction
  9.6.7*:Multi-channel imaging
  9.6.8*:Multi-channel biological and medical modeling and processing
  9.6.9*:Sensor array applications of compressive sensing
  9.6.10*:Fusion techniques for big data applications
  9.6.11*:Other applications of SAM signal processing
10:Signal Processing for Communications and Networking
 10.1:Signal Transmission and Reception
  10.1.1*:Signal detection, estimation, separation and equalization
  10.1.2*:Channel modeling and estimation, training schemes
  10.1.3*:Capacity and performance analysis/optimization
  10.1.4*:Acquisition, synchronization and tracking
  10.1.5*:Signal representation, modulation, coding and compression
  10.1.6*:Joint source-channel coding and quantization
  10.1.7*:Demodulation and decoding
  10.1.8*:Compensation of hardware impairments
  10.1.9*:Sparse signal processing for communications
 10.2:Communication Systems and Applications
  10.2.1*:Multi-carrier, OFDM, and DMT communication
  10.2.2*:CDMA and spread spectrum communication
  10.2.3*:Ultra-wideband communication
  10.2.4*:Telephone networks, DSL and powerline communication
  10.2.5*:Applications involving signal processing for communication
  10.2.6*:Underwater communication systems
  10.2.7*:Free-space optical communication
  10.2.8*:Physical layer security
  10.2.9*:Energy harvesting in communication systems
 10.3:MIMO and Multi-User MIMO Communications and Signal Processing
  10.3.1*:MIMO precoder/decoder design, receiver algorithms
  10.3.2*:MIMO channel estimation and equalization
  10.3.3*:MIMO capacity and performance analysis
  10.3.4*:Space-time coding
  10.3.5*:MIMO multi-user and multi-access schemes
  10.3.6*:Massive MIMO
 10.4:Communication Networks
  10.4.1*:Cooperative and cooordinated multi-cell techniques
  10.4.2*:Interference management techniques
  10.4.3*:Power and resource allocation
  10.4.4*:Energy management
  10.4.5*:Relaying and cooperative networks
  10.4.6*:Spectrum sensing
  10.4.7*:Cognitive radio and dynamic spectrum access
  10.4.8*:Heterogeneous networks
  10.4.9*:Ad-hoc networks
  10.4.10*:Network coding
  10.4.11*:Scheduling and queuing protocols
 10.5:Communication and sensing aspects of other networks
  10.5.1*:Distributed estimation and consensus
  10.5.2*:Collaborative signal processing
  10.5.3*:Distributed channel and source coding,
  10.5.4*:Collaborative signal processing for smart grid
  10.5.5*:Computation, communication, and control for smart grid
  10.5.6*:Communication/networking issues in social networks
  10.5.7*:Computation, communication, and control for biological networks
11:Signal Processing Theory and Methods
 11.1:Sampling and Reconstruction
  11.1.1*:Sampling theory and methods
  11.1.3*:Compressed Sampling
  11.1.4*:Nonuniform Sampling
  11.1.5*:Signal reconstruction, restoration, and enhancement
  11.1.6*:Multidimensional sampling and reconstruction
 11.2:Signal and System Modeling and Estimation
  11.2.1*:System and signal modeling: Theory, performance analysis
  11.2.2*:System identification and approximation
  11.2.3*:Multidimensional systems
  11.2.4*:Non-stationary signals and time-varying systems
  11.2.5*:Time-frequency and time-scale analysis
 11.3:Statistical Signal Processing
  11.3.1*:Detection and estimation theory and methods
  11.3.2*:Classification and pattern recognition
  11.3.3*:Cyclostationary signal analysis
  11.3.4*:Higher-order and fractional lower-order statistical methods
  11.3.5*:Performance analysis and bounds
  11.3.6*:Spectrum estimation theory and methods
  11.3.7*:Robust methods
  11.3.8*:Signal separation methods
  11.3.9*:Data driven methods (bootstrap, MCMC, sequential and particle filtering)
  11.3.10*:Non-parametric methods
  11.3.11*:Tracking algorithms
  11.3.12*:Hierarchical models & tree structured signal processing
  11.3.13*:Bayesian techniques
 11.4:Adaptive Signal Processing
  11.4.1*:Adaptive filter analysis and design
  11.4.2*:Fast algorithms for adaptive filtering
  11.4.3*:Frequency-domain and transform-based adaptive filtering
  11.4.4*:Sequential decision theory and methods
  11.4.5*:Performance analysis and bounds
  11.4.6*:Distributed and collaborative learning algorithms
 11.5:Nonlinear Systems and Signal Processing
  11.5.1*:Median, rank-order, and stack type filters
  11.5.2*:Non-Gaussian distribution filters
  11.5.3*:Polynomial and kernel methods for Signal Processing
  11.5.4*:Chaotic and fractal signals and systems
  11.5.5*:Applications of nonlinear signal processing
 11.6:Digital and Multirate Signal Processing
  11.6.1*:Algorithm analysis
  11.6.2*:Filter bank design and theory
  11.6.3*:Multirate processing and multiresolution methods
  11.6.4*:Wavelets theory and applications
  11.6.5*:Transforms for signal Processing
  11.6.6*:Fast algorithms for digital signal processing
  11.6.7*:Filter design and structures
  11.6.8*:Applications of digital and multirate signal processing
 11.7:Signal Processing Over Graphs
  11.7.1*:Statistical approaches (models, etc.)
  11.7.2*:Deterministic approaches (graph filtering, graph transforms, etc.)
  11.7.3*:Sparse graph representations
  11.7.4*:Graph analysis
  11.7.5*:Spectral graph theory and algebraic topology algorithms
  11.7.6*:Linear transforms (e.g., wavelets) over graphs
 11.8:Sparsity-aware processing
  11.8.1*:Sparse/low-dimensional parameter estimation and signal recovery
  11.8.2*:Structured low-dimensional models (joint sparsity, manifolds, low-rank, ...)
  11.8.3*:Sparsity-promoting algorithms
  11.8.4*:Dictionary learning
  11.8.5*:Robust PCA
  11.8.6*:Subspace and manifold learning
  11.8.7*:Matrix Completion
 11.9:Optimization Tools
  11.9.1*:Convex optimization and relaxation
  11.9.2*:Non-convex methods
  11.9.3*:Game theory solutions
  11.9.4*:Integer programming
  11.9.5*:Distributed optimization
 11.10:Signal Processing on Networks
  11.10.1*:Distributed processing and optimization
  11.10.2*:Social networks, social learning models
  11.10.3*:Game theoretic analysis
  11.10.4*:Learning models and game theoretic analysis
  11.10.5*:Network utility maximization, resource allocation
  11.10.6*:Detection and inference
  11.10.7*:Estimation and filtering
12:Speech Processing
 12.1:Speech Production
  12.1.1*:Physical models of the vocal production system
  12.1.2*:Singing and properties of the musical voice
 12.2:Speech Perception and Psychoacoustics
  12.2.1*:Models of Speech Perception
  12.2.2*:Hearing and Psychoacoustics
  12.2.3*:Physiological models and applications thereof
  12.2.4*:Audiology applications
 12.3:Speech Analysis
  12.3.1*:Spectral and other time-frequency analysis techniques
  12.3.2*:Distortion measures
  12.3.3*:Pitch/fundamental frequency analysis
  12.3.4*:Timing/duration/speaking rate analysis
  12.3.5*:Acoustic-phonetic features (e.g., formants etc)
  12.3.6*:Extraction of non-linguistic information (e.g., gender, emotion, etc)
  12.3.7*:Voice quality/speech disorders
 12.4:Speech Synthesis and Generation, including TTS
  12.4.1*:Segmental-Level and/or concatenative synthesis
  12.4.2*:Signal Processing/Statistical Model for synthesis
  12.4.3*:Articulatory Synthesis
  12.4.4*:Parametric Synthesis
  12.4.5*:Prosody, Emotional, and Expressive Synthesis
  12.4.6*:Text-to-phoneme conversion
  12.4.7*:Voice Quality
  12.4.8*:Voice Transformation
  12.4.9*:Audio/Visual speech synthesis
  12.4.10*:Multilingual synthesis
  12.4.11*:Quality assessent/evaluation metrics in synthesis
  12.4.12*:Tools and data for speech synthesis
  12.4.13*:Text processing for speech synthesis (text normalization, syntactic and semantic analysis)
 12.5:Speech Coding
  12.5.1*:Narrow-band and wide-band Speech Coding
  12.5.2*:Theory and techniques for signal coding (e.g., waveform, transform)
  12.5.3*:Modulation and source/channel coding
  12.5.4*:Quantization and compression
  12.5.5*:Robust coding for noisy channels
  12.5.6*:Voice Over IP (VOIP)
  12.5.7*:Quality assessent/evaluation metrics (e.g., PESQ) in coding
 12.6:Speech Enhancement
  12.6.1*:Control and reduction of channel noise (e.g., reverb, room response)
  12.6.2*:Perceptual enhancement of non-noisy speech
  12.6.3*:Speech enhancement for humans with hearing impairments
  12.6.4*:Non-acoustic microphones for enhancement
  12.6.5*:Bandwidth expansion
  12.6.6*:Noise Reduction
 12.7:Acoustic Modeling for Automatic Speech Recognition
  12.7.1*:Feature Extraction
  12.7.2*:Low-level feature modeling - Gaussians & beyond
  12.7.3*:Pronunciation modeling at the acoustic level
  12.7.4*:State clustering and novel state definitions
  12.7.5*:Prosody and other speech characteristics
  12.7.6*:Dialect, accent, and idiolect at the acoustic level
  12.7.7*:Discriminative Acoustic Training Methods for ASR
  12.7.8*:Articulatory and physiological modeling
  12.7.9*:Feature Transformation and Normalization
 12.8:Robust Speech Recognition
  12.8.1*:Features specifically for robust ASR (noise, channel, etc)
  12.8.2*:Model/backend based robust ASR
  12.8.3*:Confidence measures and rejection
  12.8.4*:Speech Activity/End-point/Barge-in detection
  12.8.5*:Non-acoustic microphones for ASR
 12.9:Speech Adaptation/Normalization
  12.9.1*:Speaker adaptation and normalization (e.g., VTLN)
  12.9.2*:Speaker adapted training methods
  12.9.3*:Environmental/Channel adaptation
  12.9.4*:Idiolect adaptation
  12.9.5*:Register and/or dialect adaptation
 12.10:General Topics in Speech Recognition
  12.10.1*:Language (LID) and dialect (DID) identification
  12.10.2*:Multilingual Speech recognition
  12.10.3*:Processing of non-native accents
 12.11:Multilingual Recognition and Identification
  12.11.1*:Pronunciation modeling at the lexical level
  12.11.2*:Dialect, accent, and idiolect at the lexical level
  12.11.3*:Multilingual aspects (e.g., unit selection)
  12.11.4*:Automatic lexicon learning
 12.12:Lexical Modeling and Access
  12.12.1*:Pronunciation modeling at the lexical level
  12.12.2*:Dialect, accent, and idiolect at the lexical level
  12.12.3*:Multilingual aspects (e.g., unit selection)
  12.12.4*:Automatic lexicon learning
 12.13:Large Vocabulary Continuous Recognition/Search
  12.13.1*:Decoding algorithms and implementation
  12.13.3*:Multi-pass strategies
  12.13.4*:Miscellaneous Topics
 12.14:Speaker Recognition and Characterization
  12.14.1*:Features and characteristics for speaker recognition
  12.14.2*:Robustness to variable and degraded channels
  12.14.3*:Verification, identification, segmentation, and clustering
  12.14.4*:Speaker characterization and adaptation
  12.14.5*:Speaker recognition with speech recognition
  12.14.6*:Speaker confidence estimation
  12.14.7*:Multimodal and multimedia human speaker recognition
  12.14.8*:Corpora, annotation, evaluation, and other resources
  12.14.9*:Higher-level knowledge in speaker recognition
  12.14.10*:Speaker localization (space) (e.g., in meetings)
  12.14.11*:Speaker diarization (time) (e.g., in meetings)
  12.14.12*:Speaker clustering (e.g., in Broadcast news)
 12.15:Resource constrained speech recognition
  12.15.1*:Low-power speech recognition
  12.15.2*:Reduced computation speech recognition
  12.15.3*:ASR techniques for highly portable/mobile devices
13:Human Language Technology
 13.1:Spoken Language Understanding
  13.1.1*:Semantic classification
  13.1.2*:Entity extraction from speech
  13.1.3*:Spoken document summarization
  13.1.4*:Topic spotting and classification
  13.1.5*:Question/answering from speech
  13.1.6*:Paralinguistic (emotion, age, gender, rate, etc.) information
  13.1.7*:Nonlinguistic (meaning external to language) information, gestures, etc.
  13.1.8*:Detecting linguistic/discourse structure (e.g., disfluencies, sentence/topic boundaries, speech acts)
  13.1.9*:Relation to and interpretation of sign language
 13.2:Human Spoken Language Acquisition, Development and Learning
  13.2.1*:Language acquisition, development, and learning models
  13.2.2*:Computer aids for language learning
  13.2.3*:Attributes and modeling techniques for assessment of language fluency
 13.3:Spoken and Multimodal Dialog Systems and Applications
  13.3.1*:Spoken and multimodal dialog systems, applications, and architectures
  13.3.2*:Stochastic Learning for dialog modeling
  13.3.3*:Response Generation
  13.3.4*:Technologies for specific population groups, e.g., children, aged, impaired, and universal access
  13.3.5*:Evaluation metrics and standards
  13.3.6*:Speech/voice-based human-computer interfaces (HCI)
  13.3.7*:Other applications
 13.4:Speech Data Mining
  13.4.1*:Analysis, Tools, Evaluations, and Applications for mining spoken data
  13.4.2*:Speech data mining theory, algorithms, and methods
  13.4.3*:Mining heterogeneous speech and multimedia data
 13.5:Machine Translation of Speech
  13.5.1*:Semi-automatic and data driven methods
  13.5.2*:Speech processing for MTS
  13.5.3*:Corpora, annotation, and other resources
  13.5.4*:Interlingua and transfer approaches
  13.5.5*:Integration of speech and linguistic processing
  13.5.6*:Machine transliteration for named entities
  13.5.7*:Evaluation metrics (e.g., BLEU)
  13.5.8*:Systems and applications for MTS
 13.6:Language Modeling, for Speech and HLT
  13.6.1*:N-grams, their generalizations and smoothing methods.
  13.6.2*:Language Model Adaptation
  13.6.3*:Grammar based language modeling
  13.6.4*:Maxent and feature based language modeling
  13.6.5*:Dialect, accent, and idiolect at the language level
  13.6.6*:Discriminative LM Training Methods
  13.6.7*:Representation learning approaches to LM, e.g., deep learning
  13.6.8*:Other approaches to LMs
 13.7:Speech Retrieval
  13.7.1*:Spoken term detection
  13.7.2*:Search/retrieval of speech documents
  13.7.3*:Voice search
 13.8:Spoken language resources and annotation
  13.8.1*:General corpora, annotation, and other resources
14:Signal Processing for Big Data
 14.1:Computational models and representations for big data
  14.1.1*:Compressive sampling for big data
  14.1.2*:Tensor factorization models for multi-way data
  14.1.3*:Randomized linear algebra for big data
  14.1.4*:Scalable (fast)
  14.1.5*:Spectral decompositions for representation of big data
  14.1.6*:Graph signal processing theory
  14.1.7*:Transforms for graph signals
  14.1.8*:Graph simplification and multi-resolution methods
 14.2:Big data acquisition, storage, retrieval, interpretation
  14.2.1*:Protocols for networked storage, indexing and retrieval
  14.2.2*:Signal processing hardware and architectures for massive datasets
  14.2.3*:Data resiliency to node failure
  14.2.4*:Lossless data compression for massive datasets
  14.2.5*:Lossy data compression for massive datasets
  14.2.6*:Sketching, streaming, and real time data retrieval for time varying (spatio-temporal) data
 14.3:Learning and inference with big data
  14.3.1*:High dimensional spatio-temporal models
  14.3.2*:Theoretical limits of high dimensional statistical inference
  14.3.3*:Methods of anomaly/change detection with time varying big data
  14.3.4*:Random matrix models and non-commutative information theory for big data
  14.3.5*:Statistical modeling of heterogeneous data types
  14.3.6*:Learning correlation networks for big data
  14.3.7*:Learning Bayes networks for big data
  14.3.8*:Deep learning for big data
  14.3.9*:Non-parametric learning for big data
  14.3.10*:Crowdsourcing/human computation for big data processing
  14.3.11*:Stream Mining and Decision Making from Big Data
  14.3.12*:Signal processing approaches to discovery/creativity/machine science
 14.4:SP Methods for Big Data Analytics
  14.4.1*:Visualization and summarization of big data
  14.4.2*:Social media, recommendation systems and collaborative filtering
  14.4.3*:Defense, intelligence and security
  14.4.4*:Biology and medicine
  14.4.5*:Astronomy and other physical sciences
  14.4.6*:Urban informatics
  14.4.7*:Big Data in Social sciences
  14.4.8*:Business analytics, forensics and finance
 14.5:Distributed signal and information processing for big data on networks
  14.5.1*:Distributed processing over heterogeneous networks
  14.5.2*:Distributed processing over time-varying networks
  14.5.3*:Distributed algorithms for processing big data on networks
  14.5.4*:Distributed detection and estimation
  14.5.5*:Distributed control, optimization and learning
  14.5.6*:Distributed storage, indexing and retrieval
15:Signal Processing for Internet of Things
 15.1:IOT Communication and networking
  15.1.1*:Signal processing issues in IoT with 5G and beyond
  15.1.2*:mm-wave based IoT systems
  15.1.3*:Wired and wireless M2M Communication and networking
  15.1.4*:Energy-efficient communication
  15.1.5*:Spectrum efficiency and management for IoT
 15.2:IOT Information Processing¬†
  15.2.1*:Low-power, Distributed data processing on sensors
  15.2.2*:Intelligent signal and information processing
  15.2.3*:Data mining
  15.2.4*:Information fusion
  15.2.5*:Processing algorithms and theories for IoT
  15.2.6*:Cross-layer processing for IoT
 15.3:IOT Security
  15.3.1*:Cyber security for IOT
  15.3.2*:Reliability for IOT
  15.3.3*:Privacy perseverance and trust for IOT
 15.4:IOT Systems
  15.4.1*:Human-cyber-physical interaction
  15.4.2*:Sensing, networking and computing with smartphones and wearable devices
  15.4.3*:Computing and processing platforms for IoT Implementations
  15.4.4*:Programing and Developing Tools to enable IoT
  15.4.5*:Quality of Experiences and Quality of Services in IoT applications
  15.4.6*:Prototypes, test-beds and field trials on smart services and applications, e.g., Smart cities, intelligent transportation, building automation, assisted living, e-health, etc
16:Signal Processing (SP) Education
 16.1*:Novel laboratory, computer-based, and distance teaching methods
 16.2*:New SP pedagogy, including MOOCs and flipped classes
 16.3*:New technologies in SP education
 16.4*:SP across the engineering curriculum
 16.5*:SP curriculum issues (early/late, simulation/real-time, theory/practice)
 16.6*:Industry and SP education: Linking academic knowledge with industrial needs
 16.7*:Educational practices on signal acquisition, conditioning, and other analog issues
 16.8*:Teaching embedded systems and other hardware for processing signals
 16.9*:SP outreach programs
 16.10*:Education strategies to encourage participation of women and underrepresented students in SP careers
 16.11*:SP tips and tricks
17:Computational Imaging
 17.1:IMT Computational Imaging Methods and Models
  17.1.1*:IMT-CIS Coded Image Sensing
  17.1.2*:IMT-CST Compressed Sensing
  17.1.3*:IMT-SIM Statistical Image Models
  17.1.4*:IMT-SLM Sparse and Low Rank Models
  17.1.5*:IMT-GIM Graphical Image Models
  17.1.6*:IMT-LBM Learning-Based Models
  17.1.7*:IMT-PIM Perceptual Image Models
 17.2:CIF Computational Image Formation
  17.2.1*:CIF-SBR Sparsity-Based Reconstruction
  17.2.2*:CIF-SBI Statistically-Based Inversion
  17.2.3*:CIF-MIF Multi-Image & Sensor Fusion
  17.2.4*:CIF-OBI Optimization-based Inversion Methods
 17.3:CIS Computational Imaging Systems
  17.3.1*:CIS-CPH Computational Photography
  17.3.2*:CIS-MIS Mobile Imaging
  17.3.3*:CIS-PIS Pervasive Imaging
  17.3.4*:CIS-HCC Human Centric Computing
  17.3.5*:CIS-CMI Computational Microscopy
  17.3.6*:CIS-SSI Spectral Sensing
  17.3.7*:CIS-TIM Tomographic Imaging
  17.3.8*:CIS-MRI Magnetic Resonance Imaging
  17.3.9*:CIS-AIM Acoustic Imaging
  17.3.10*:CIS-RIM Radar Imaging
  17.3.11*:CIS-NCI Novel Computational Imaging Systems
 17.4:HSS Computational Imaging Hardware and Software
  17.4.1*:HSS-HPC High-performance embedded computing systems
  17.4.2*:HSS-BDC Big Data Computational Imaging
  17.4.3*:HSS-HDD Integrated Hardware/Digital Design
  17.4.4*:HSS-NSS Non-traditional Sensor Systems