Paper Topic
Choose a submission topic for your paper.
Choose a session topic in track: Audio and Acoustic Signal Processing
1.1: Room Acoustics and Acoustic System Modeling
1.2: Transducers
1.3: Loudspeaker and Microphone Array Signal Processing
1.4: Active Noise Control
1.5: Echo Cancellation
1.6: Auditory Modeling and Hearing Aids
1.7: Source Separation and Signal Enhancement
1.8: Spatial and Multichannel Audio
1.9: Audio Coding
1.10: Audio Analysis and Synthesis
1.11: Content-Based Audio Processing
1.12: Audio for Multimedia
1.13: Network Audio
1.14: Audio Processing Systems
1.15: Bioacoustics and Medical Acoustics
1.16: Music Signal Processing
Choose a session topic in track: 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
2.2.1: Segmentation
2.2.2: Registration
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: Bioinformatics
2.5.1: Genomics and proteomics
2.5.2: Computational biology and biological networks
Choose a session topic in track: Image, Video, and Multidimensional Signal Processing
3.1: Image/Video Coding
3.1.1: Still Image Coding
3.1.2: Video Coding
3.1.3: Stereoscopic and 3-D Coding
3.1.4: Distributed Source Coding
3.1.5: Image/Video Transmission
3.2: Image/Video Processing
3.2.1: Image Filtering
3.2.2: Restoration
3.2.3: Enhancement
3.2.4: Image Segmentation
3.2.5: Video Segmentation and Tracking
3.2.6: Morphological Processing
3.2.7: Stereoscopic and 3-D Processing
3.2.8: Image Feature Extraction
3.2.9: Image Analysis
3.2.10: Video Feature Extraction
3.2.11: Video Analysis
3.2.12: Modeling
3.2.13: Biometrics
3.2.14: Interpolation and Super-resolution
3.2.15: Motion Detection and Estimation
3.3: Image Formation
3.3.1: Remote Sensing Imaging
3.3.2: Geophysical and Seismic Imaging
3.3.3: Optical Imaging
3.3.4: Synthetic-Natural Hybrid Image Systems
3.4: Image Scanning, Display, and Printing
3.4.1: Scanning and Sampling
3.4.2: Quantization and Halftoning
3.4.3: Color Reproduction
3.4.4: Image Representation and Rendering
3.4.5: Display and Printing Systems
3.4.6: Image Quality Assessment
3.5: Image/Video Storage, Retrieval
3.5.1: Image and Video Databases
3.5.2: Image Indexing and Retrieval
3.5.3: Video Indexing, Retrieval and Editing
Choose a session topic in track: Design and Implementation of Signal Processing Systems
4.1: Algorithm and architecture co-optimization
4.2: Compilers and tools for DSP implementation
4.3: DSP algorithm implementation in hardware and software
4.4: Low-power signal processing techniques and architectures
4.5: Programmable and reconfigurable DSP architectures
4.6: System-on-chip architectures for signal processing
Choose a session topic in track: Industry Technology Track
5.1: DSP Chips and Architectures
5.1.1: Mixed Signal Processing
5.1.2: Special-Purpose and FPGA DSPs
5.1.3: Host-Based Signal Processing
5.1.4: Multiprocessor Architectures
5.2: DSP Tools and Rapid Prototyping
5.2.1: DSP Simulation Tools
5.2.2: Rapid Prototyping and languages
5.2.3: DSP Libraries
5.2.4: Operating Systems
5.3: Communication Technologies
5.3.1: Cellular and Satellite Telephony
5.3.2: Data Communications and Networking
5.3.3: Sortware-Defined Radios
5.3.4: Vocoders
5.3.5: Power Line Communication
5.3.6: RFID
5.4: Speech Processing Applications
5.4.1: Speaker Recognition
5.4.2: Speech Compression
5.4.3: Speech Enhancement
5.4.4: Speech Recognition
5.4.5: Speech Synthesis
5.5: Multimedia and DTV Technologies
5.5.1: DSP Implementations of Music, Speech, and Audio
5.5.2: Image and Video Applications
5.5.3: Standards and Format Conversions
5.5.4: Internet and Teleconferencing
5.6: Adaptive Interference Cancellation
5.6.1: Smart Antennas
5.6.2: Active Sound Reduction
5.6.3: Acoustic and Electrical Noise and Echo Cancellation
5.6.4: Hands-Free Telephony
5.7: Automotive Applications
5.7.1: Intelligent Dashboards, Vehicles, and Highways (IVHS)
5.7.2: Engine Management
5.7.3: Route Planning and Tracking
5.7.4: New Consumer Applications
5.8: Defense and Security Applications
5.8.1: Optical Correlation
5.8.2: Decluttering Target Identification and Tracking
5.8.3: DSP-Based Cryptography, Stenography, and Watermarking
5.8.4: Radar and Sonar
5.9: Emerging DSP Applications
5.9.1: Biometrics
5.9.2: Biomedical
5.9.3: Power Systems and Motor Controls
5.9.4: Machine Learning
5.10: Other ITT Topics
Choose a session topic in track: Information Forensics and Security
6.1: Watermarking and Steganography
6.1.1: Theoretical models
6.1.2: Algorithms
6.1.3: Benchmarking and security analysis
6.1.4: Steganography and steganalysis
6.2: Multimedia Forensics
6.2.1: Sensor and channel forensics
6.2.2: Tamper detection
6.2.3: Anti-forensics and countermeasures
6.2.4: Plagiarism and near-duplicate detection
6.2.5: Robust hashing
6.3: Biometrics
6.3.1: Biometric methods and modalities
6.3.2: Biometric security
6.3.3: Performance and evaluation
6.4: Communications and Network Security
6.4.1: Jamming and anti-jamming
6.4.2: Covert or stealthy communication
6.4.3: Secret key extraction from channels
6.4.4: Information theoretic security
6.4.5: Network attacks, protection and monitoring
6.5: Signal Processing and Cryptography
6.5.1: Multimedia encryption
6.5.2: Signal processing in the encrypted domain
6.5.3: Traitor tracing codes
6.5.4: Visual secret sharing
6.5.5: Side channel attacks
6.5.6: Privacy protection
6.6: Applications
6.6.1: Surveillance
6.6.2: Content protection, identification and monitoring
6.6.3: Cloud and distributed computing systems
6.6.4: Smart grid and power/energy systems
6.6.5: Social media and network systems
Choose a session topic in track: Machine Learning for Signal Processing
7.1: Other applications of machine learning (MLR-APPL)
7.2: Bayesian learning; Bayesian signal processing (MLR-BAYL)
7.3: Cognitive information processing (MLR-COGP)
7.4: Distributed and Cooperative Learning (MLR-DIST)
7.5: Applications in Data Fusion (MLR-FUSI)
7.6: Graphical and kernel methods (MLR-GRKN)
7.7: Independent component analysis (MLR-ICAN)
7.8: Information-theoretic learning (MLR-INFO)
7.9: Learning theory and algorithms (MLR-LEAR)
7.10: Applications in Music and Audio Processing (MLR-MUSI)
7.11: Neural network learning (MLR-NNLR)
7.12: Pattern recognition and classification (MLR-PATT)
7.13: Bounds on performance (MLR-PERF)
7.14: Sequential learning; sequential decision methods (MLR-SLER)
7.15: Source separation (MLR-SSEP)
7.16: Applications in Systems Biology (MLR-SYSB)
Choose a session topic in track: Multimedia Signal Processing
8.1: Multimodal signal processing
8.1.1: Joint processing/presentation of audio-visual information
8.1.2: Synchronization of audio and visual data
8.1.3: Fusion/fission of sensor information or multimodal data
8.1.4: Integration of media, art, and multimedia technology
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: Virtual reality and mixed-reality in networked environments
8.3: Multimedia communications and networking
8.3.1: Wireless and mobile multimedia communication
8.3.2: Media streaming, media content distribution, and storage
8.3.3: Quality of service provisioning
8.3.4: Cross-layer design for multimedia communication
8.3.5: Overlay, peer-to-peer, and peer-assisted networking for multimedia
8.3.6: Home networking for multimedia
8.3.7: Location-aware multimedia computing
8.3.8: Multimedia sensor and ad hoc networks
8.3.9: Media compression and related standardization activities
8.3.10: Multimedia watermarking
8.3.11: Distributed source and source-channel coding
8.4: Multimedia security and content protection
8.4.1: Data hiding
8.4.2: Authentication
8.4.3: Access control
8.4.4: Single and multi-media security
8.4.5: Multimedia forensics
8.4.6: Security applications of watermarking and fingerprinting
8.5: Multimedia human-machine interface and interaction
8.5.1: Human perception modelling
8.5.2: Modeling of multimodal perception
8.5.3: Human-human and human-computer dialog
8.5.4: Multimodal interfaces
8.5.5: Brain-computer interfaces
8.6: Quality Assessment
8.6.1: Subjective visual quality assessment
8.6.2: Objective visual quality assessment
8.6.3: Subjective auditory quality assessment
8.6.4: Objective auditory quality assessment
8.6.5: Evaluation of user experience, cross-modal assessment
8.6.6: Standardization activities
8.7: Multimedia databases and digital libraries
8.7.1: Visual indexing, analysis and representation
8.7.2: Audio indexing, analysis and representation
8.7.3: Content-based and context-based information retrieval
8.7.4: Knowledge and semantics in media annotation and retrieval
8.7.5: Fingerprinting and duplicate detection
8.8: Multimedia computing systems and applications
8.8.1: Multimedia system design
8.8.2: Distributed multimedia systems
8.8.3: Entertainment and gaming
8.8.4: e-Health and telemedicine
8.8.5: IP video/web conferencing
8.8.6: e-learning
8.9: Hardware and software for multimedia systems
8.9.1: Multimedia hardware design
8.9.2: Real-time multimedia systems
8.9.3: Implementations on graphics processing units (GPUs)
8.9.4: Implementations on general-purpose processors, multimedia processors, DSPs, multi-core processors
8.9.5: Implementations in portable/wearable systems
8.9.6: Power-aware systems for multimedia
8.10: Haptic technology and interaction
8.10.1: Processing and rendering of haptic signals
8.10.2: Compression and transmission of haptic signals
8.10.3: Audio-visual-haptic environments
8.10.4: Multimedia applications using haptics
8.11: Bio-inspired multimedia systems and signal processing
8.11.1: Bio-inspired signal processing for multimedia
8.11.2: Multimodal signal fusion in humans and animals
8.11.3: Joint bio-inspired and conventional multimedia signal processing
Choose a session topic in track: Sensor Array and Multichannel Signal Processing
9.1: Sensor Array Processing
9.1.1: Beamforming
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, separation, classification, and tracking
9.1.9: Blind 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
9.3: Multi-channel Signal Processing
9.3.1: Channel modelling 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
9.5: Sensor and Relay Networks
9.5.1: Sensor and relay network signal processing
9.5.2: Network beamforming and coding
9.5.3: Distributed and cooperative processing
9.5.4: Data fusion and decision fusion from multiple sensor types
9.5.5: Multi-Sensor processing for smart grid and energy systems
9.6: 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: Multi-channel imaging
9.6.5: Multi-channel biological and medical modelling and processing
9.6.6: Other applications of SAM signal processing
Choose a session topic in track: Signal Processing Education
10.1: Signal Processing Education
Choose a session topic in track: Signal Processing for Communications and Networking
11.1: Signal Transmission and Reception
11.1.1: Signal detection, estimation, separation and equalization
11.1.2: Channel modeling and estimation, training schemes
11.1.3: Capacity and performance analysis/optimization
11.1.4: Acquisition, synchronization and tracking
11.1.5: Signal representation, modulation, coding and compression
11.1.6: Joint source-channel coding and quantization, iterative decoding algorithms
11.2: Communication Systems and Applications
11.2.1: Multi-carrier, OFDM, and DMT communication
11.2.2: Multi-rate, CDMA and spread spectrum communication
11.2.3: Ultra wideband communication
11.2.4: Telephone networks, DSL and powerline communication
11.2.5: Applications involving signal processing for communication
11.2.6: Computation, Communication, and Control for Smart Grid
11.2.7: Communication/Networking Issues in Social Networks
11.2.8: Computation, Communication, and Control for Biological Networks
11.2.9: Underwater Communication Systems
11.2.10: Visible Light Communication Systems
11.2.11: Free Space Optical Communication
11.3: MIMO Communications and Signal Processing
11.3.1: MIMO precoder/decoder design, receiver algorithms
11.3.2: MIMO channel estimation and equalization
11.3.3: MIMO capacity and performance
11.3.4: MIMO space-time code design, analysis and decoding algorithms
11.3.5: MIMO multi-user and multi-access schemes
11.4: Communication and Sensing aspects of Sensor Networks, Wireless and Ad-Hoc Networks
11.4.1: Distributed and collaborative signal processing
11.4.2: Distributed channel and source coding, information-theoretic studies
11.4.3: Ad-hoc wireless networks
11.4.4: Physical layer issues, cross-layer design
11.4.5: Scheduling and queuing protocols
11.4.6: Power control, resource management, system level optimization
11.4.7: Cognitive Radio and Dynamic Spectrum Access
11.4.8: Collaborative Signal Processing for Smart Grid
Choose a session topic in track: Signal Processing Theory and Methods
12.1: Sampling and Reconstruction
12.1.1: Sampling theory and methods
12.1.2: Quantization
12.1.3: Extrapolation and interpolation
12.1.4: Signal reconstruction, restoration and enhancement
12.1.5: Multidimensional sampling and reconstruction
12.2: Signal and System Modeling, Representation and Estimation
12.2.1: System modeling
12.2.2: Signal and noise modeling
12.2.3: System identification and approximation
12.2.4: Multidimensional systems
12.2.5: Non-stationary signals and time-varying systems
12.2.6: Time-frequency and time-scale analysis
12.2.7: Blind and semi-blind source separation
12.3: Statistical Signal Processing
12.3.1: Detection and estimation theory and methods
12.3.2: Classification and pattern recognition
12.3.3: Cyclostationary signal analysis
12.3.4: Higher-order and fractional lower-order statistical methods
12.3.5: Performance analysis and bounds
12.3.6: Spectrum estimation theory and methods
12.3.7: Robust methods
12.3.8: Independent component analysis
12.3.9: Monte-Carlo based signal processing methods
12.4: Adaptive Signal Processing
12.4.1: Adaptive filter analysis and design
12.4.2: Fast algorithms for adaptive filtering
12.4.3: Frequency-domain and transform-based adaptive filtering
12.4.4: Sequential decision theory and methods
12.4.5: Performance analysis and bounds
12.4.6: Distributed and collaborative signal processing
12.5: Nonlinear Systems and Signal Processing
12.5.1: Median, rank-order and stack type filters
12.5.2: Non-Gaussian distribution filters
12.5.3: Nonlinear signal and system models
12.5.4: Nonlinear random process models
12.5.5: Nonlinear adaptive filters
12.6: Filter Design
12.6.1: Filter design criteria and optimization methods
12.6.2: Filter architectures
12.6.3: Performance analysis
12.7: Multirate Signal Processing
12.7.1: Multirate architectures
12.7.2: Filterbanks and wavelets
12.7.3: Multirate processing and multiresolution methods
12.7.4: Hierarchical models and tree-structured signal processing
Choose a session topic in track: Speech Processing
13.1: Speech Production (SPE-SPRD)
13.1.1: Physical models of the vocal production system
13.1.2: Singing and properties of the musical voice
13.2: Speech Perception and Psychoacoustics (SPE-SPER)
13.2.1: Models of Speech Perception
13.2.2: Hearing and Psychoacoustics
13.2.3: Physiological models and applications thereof
13.2.4: Audiology applications
13.3: Speech Analysis (SPE-ANLS)
13.3.1: Spectral and other time-frequency analysis techniques
13.3.2: Distortion measures
13.3.3: Pitch/fundamental frequency analysis
13.3.4: Timing/duration/speaking rate analysis
13.3.5: Acoustic-phonetic features (e.g., formants etc)
13.3.6: Extraction of non-linguistic information (e.g., gender, emotion, etc)
13.3.7: Voice quality/speech disorders
13.4: Speech Synthesis and Generation, including TTS (SPE-SYNT)
13.4.1: Segmental-Level and/or concatenative synthesis
13.4.2: Signal Processing/Statistical Model for synthesis
13.4.3: Articulatory Synthesis
13.4.4: Parametric Synthesis
13.4.5: Prosody, Emotional, and Expressive Synthesis
13.4.6: Text-to-phoneme conversion
13.4.7: Voice Quality
13.4.8: Voice Transformation
13.4.9: Audio/Visual speech synthesis
13.4.10: Multilingual synthesis
13.4.11: Quality assessent/evaluation metrics in synthesis
13.4.12: Tools and data for speech synthesis
13.4.13: Text processing for speech synthesis (text normalization, syntactic and semantic analysis)
13.5: Speech Coding (SPE-CODI)
13.5.1: Narrow-band and wide-band Speech Coding
13.5.2: Theory and techniques for signal coding (e.g., waveform, transform)
13.5.3: Modulation and source/channel coding
13.5.4: Quantization and compression
13.5.5: Robust coding for noisy channels
13.5.6: Voice Over IP (VOIP)
13.5.7: Quality assessent/evaluation metrics (e.g., PESQ) in coding
13.6: Speech Enhancement (SPE-ENHA)
13.6.1: Control and reduction of channel noise (e.g., reverb, room response)
13.6.2: Perceptual enhancement of non-noisy speech
13.6.3: Speech enhancement for humans with hearing impairments
13.6.4: Non-acoustic microphones for enhancement
13.6.5: Bandwidth expansion
13.6.6: Noise Reduction
13.7: Acoustic Modeling for Automatic Speech Recognition (SPE-RECO)
13.7.1: Feature Extraction
13.7.2: Low-level feature modeling - Gaussians & beyond
13.7.3: Pronunciation modeling at the acoustic level
13.7.4: State clustering and novel state definitions
13.7.5: Prosody and other speech characteristics
13.7.6: Dialect, accent, and idiolect at the acoustic level
13.7.7: Discriminative Acoustic Training Methods for ASR
13.7.8: Articulatory and physiological modeling
13.7.9: Feature Transformation and Normalization
13.8: Robust Speech Recognition (SPE-ROBU)
13.8.1: Features specifically for robust ASR (noise, channel, etc)
13.8.2: Model/backend based robust ASR
13.8.3: Confidence measures and rejection
13.8.4: Speech Activity/End-point/Barge-in detection
13.8.5: Non-acoustic microphones for ASR
13.9: Speech Adaptation/Normalization (SPE-ADAP)
13.9.1: Speaker adaptation and normalization (e.g., VTLN)
13.9.2: Speaker adapted training methods
13.9.3: Environmental/Channel adaptation
13.9.4: Idiolect adaptation
13.9.5: Register and/or dialect adaptation
13.10: General Topics in Speech Recognition (SPE-GASR)
13.10.1: Distributed Speech Recognition - Client/Server methods
13.10.2: Alternative Statistical/Machine Learning Methods (e.g., no HMMs)
13.10.3: Word spotting
13.10.4: Metadata (e.g., emotion, speaker, accent) extraction from acoustics
13.10.5: New algorithms, computational strategies, data- structures for ASR
13.10.6: Multi-modal (such as audio-visual) speech recognition
13.10.7: Corpora, annotation, and other resources
13.10.8: Algorithm approximation methods in ASR
13.10.9: Structured classification approaches
13.11: Multilingual Recognition and Identification (SPE-MULT)
13.11.1: Language (LID) and dialect (DID) identification
13.11.2: Multilingual Speech recognition
13.11.3: Processing of non-native accents
13.12: Lexical Modeling and Access (SPE-LEXI)
13.12.1: Pronunciation modeling at the lexical level
13.12.2: Dialect, accent, and idiolect at the lexical level
13.12.3: Multilingual aspects (e.g., unit selection)
13.12.4: Automatic lexicon learning
13.13: Large Vocabulary Continuous Recognition/Search (SPE-LVCR)
13.13.1: Decoding algorithms and implementation
13.13.2: Lattices
13.13.3: Multi-pass strategies
13.13.4: Miscellaneous Topics
13.14: Speaker Recognition and Characterization (SPE-SPKR)
13.14.1: Features and characteristics for speaker recognition
13.14.2: Robustness to variable and degraded channels
13.14.3: Verification, identification, segmentation, and clustering
13.14.4: Speaker characterization and adaptation
13.14.5: Speaker recognition with speech recognition
13.14.6: Speaker confidence estimation
13.14.7: Multimodal and multimedia human speaker recognition
13.14.8: Corpora, annotation, evaluation, and other resources
13.14.9: Higher-level knowledge in speaker recognition
13.14.10: Speaker localization (space) (e.g., in meetings)
13.14.11: Speaker diarization (time) (e.g., in meetings)
13.14.12: Speaker clustering (e.g., in Broadcast news)
13.15: Resource constrained speech recognition (SPE-RCSR)
13.15.1: Low-power speech recognition
13.15.2: Reduced computation speech recognition
13.15.3: ASR techniques for highly portable/mobile devices
Choose a session topic in track: Spoken Language Processing
14.1: Spoken Language Understanding (SLP-UNDE)
14.1.1: Semantic classification
14.1.2: Entity extraction from speech
14.1.3: Spoken document summarization
14.1.4: Topic spotting and classification
14.1.5: Question/answering from speech
14.1.6: Paralinguistic (emotion, age, gender, rate, etc.) information
14.1.7: Nonlinguistic (meaning external to language) information, gestures, etc.
14.1.8: Detecting linguistic/discourse structure (e.g., disfluencies, sentence/topic boundaries, speech acts)
14.1.9: Relation to and interpretation of sign language
14.2: Human Spoken Language Acquisition, Development and Learning (SLP-LADL)
14.2.1: Language acquisition, development, and learning models
14.2.2: Computer aids for language learning
14.2.3: Attributes and modeling techniques for assessment of language fluency
14.3: Spoken and Multimodal Dialog Systems and Applications (SLP-SMMD)
14.3.1: Spoken and multimodal dialog systems, applications, and architectures
14.3.2: Stochastic Learning for dialog modeling
14.3.3: Response Generation
14.3.4: Technologies for the aged
14.3.5: Evaluation metrics and standards
14.3.6: Speech/voice-based human-computer interfaces (HCI)
14.3.7: Speech HCI for individuals with impairments (blindness, etc.) and universal access (UA)
14.3.8: Other applications
14.4: Speech Data Mining (SLP-DM)
14.4.1: Analysis, Tools, Evaluations, and Applications for mining spoken data
14.4.2: Speech data mining theory, algorithms, and methods
14.4.3: Mining heterogeneous speech and multimedia data
14.5: Speech Retrieval (SLP-IR)
14.5.1: Spoken term detection
14.5.2: Search/retrieval of speech documents
14.5.3: Voice search
14.6: Machine Translation of Speech (SLP-SSMT)
14.6.1: Semi-automatic and data driven methods
14.6.2: Speech processing for MTS
14.6.3: Corpora, annotation, and other resources
14.6.4: Interlingua and transfer approaches
14.6.5: Integration of speech and linguistic processing
14.6.6: Machine transliteration for named entities
14.6.7: Evaluation metrics (e.g., BLEU)
14.6.8: Systems and applications for MTS
14.7: Language Modeling, for Speech and SLP (SLP-LANG)
14.7.1: N-grams, their generalizations and smoothing methods.
14.7.2: Language Model Adaptation
14.7.3: Grammar based language modeling
14.7.4: Maxent and feature based language modeling
14.7.5: Dialect, accent, and idiolect at the language level
14.7.6: Discriminative LM Training Methods
14.7.7: Other approaches to LMs
14.7.8: Structured classification approaches
14.8: Spoken language resources and annotation (SLP-REAN)
14.8.1: General corpora, annotation, and other resources
Session Topic
Note: First select the primary track, then select the actual submission topic.
Select a primary track
1: Audio and Acoustic Signal Processing
2: Bio Imaging and Signal Processing
3: Image, Video, and Multidimensional Signal Processing
4: Design and Implementation of Signal Processing Systems
5: Industry Technology Track
6: Information Forensics and Security
7: Machine Learning for Signal Processing
8: Multimedia Signal Processing
9: Sensor Array and Multichannel Signal Processing
10: Signal Processing Education
11: Signal Processing for Communications and Networking
12: Signal Processing Theory and Methods
13: Speech Processing
14: Spoken Language Processing
Secondary Review Topic (optional)
Note: The secondary review topic is optional, but helps the technical program committee better plan for your submission.
Select a secondary track
1: Audio and Acoustic Signal Processing
2: Bio Imaging and Signal Processing
3: Image, Video, and Multidimensional Signal Processing
4: Design and Implementation of Signal Processing Systems
5: Industry Technology Track
6: Information Forensics and Security
7: Machine Learning for Signal Processing
8: Multimedia Signal Processing
9: Sensor Array and Multichannel Signal Processing
10: Signal Processing Education
11: Signal Processing for Communications and Networking
12: Signal Processing Theory and Methods
13: Speech Processing
14: Spoken Language Processing