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|AUDIO AND ACOUSTIC SIGNAL PROCESSING|
|AUD-MAAE||Modeling, Analysis and Synthesis of Acoustic Environments
Acoustic system modeling; room response measurement, modeling and simulation; room geometry inference; reflector localization; reverberation time estimation; direct-to-reverberation ratio estimation.
|AUD-CLAS||Detection and Classification of Acoustic Scenes and Events
Acoustic scene classification and detection; acoustic event detection and classification; environmental audio analysis.
|AUD-AMHI||Auditory Modeling and Hearing Instruments
Human audition and psychoacoustics; binaural hearing; computational auditory scene analysis; perceptual and psychophysical models of audio algorithms and systems; hearing aids; cochlear implants; signal processing in hearing instruments.
|AUD-ASAP||Acoustic Sensor Array Processing
Far-field and near-field beamforming; acoustic sensor array processing; speech enhancement using acoustic sensor arrays; source localization and tracking; simultaneous localization and mapping of sources and sensors; time-delay estimation; array calibration; distributed and ad-hoc microphone arrays; deep learning methods for acoustic array processing.
|AUD-NEFR||Active Noise Control, Echo Reduction and Feedback Reduction
Active noise cancellation and suppression; Single-channel and multichannel acoustic echo cancellation; echo path estimation and modeling; echo suppression; nonlinear echo reduction; double-talk detection; adaptive filter theory for audio applications; adaptive techniques for feedforward control; feedback cancellation; feedback suppression; transducer modeling for noise control and echo/feedback reduction.
|AUD-SIRR||System Identification and Reverberation Reduction
SIMO and MIMO identification; reverberation cancellation and suppression; blind deconvolution; channel shortening; channel equalization.
|AUD-SEP||Audio and Speech Source Separation
Single-channel and multichannel source separation; computational acoustic scene analysis; NMF-based source separation; deep learning methods for source separation.
|AUD-SEN||Signal Enhancement and Restoration
Noise reduction; noise estimation, compensation, and equalization; deep learning methods for signal enhancement and restoration; audio de-noising and restoration; bandwidth expansion; clipping restoration, near-end listening enhancement.
|AUD-QIM||Quality and Intelligibility Measures
Perceptual measures of audio quality; objective and subjective quality assessment; network audio quality assessment; speech intelligibility measures.
|AUD-SARR||Spatial Audio Recording and Reproduction
Analysis and synthesis of sound fields; wave-field synthesis; loudspeaker array processing; Ambisonics; panning; multipoint synthesis and binaural synthesis; crosstalk cancellation; virtual auditory environments; Auralization, spatialization and virtualization; measurement and modeling of head-related transfer functions; binaural rendering; artificial reverberation algorithms. Loudspeaker equalization and room compensation.
|AUD-AMCT||Audio and Speech Modeling, Coding and Transmission
Sparse representations; Probabilistic modeling; Low bit-rate and high-quality audio coding; scalable and lossless audio coding; spatial audio coding; joint source-channel coding; signal representations for coding; parametric and structured audio coding; psychoacoustic models for coding; low-delay audio coding; error detection, correction, and concealment.
|AUD-MSP||Music Signal Analysis, Processing and Synthesis
Analysis; modification; synthesis; models and representations for musical signals; pitch and multi-pitch estimation; audio feature extraction; melody, note, chord, key, and rhythm estimation and detection; automatic transcription; musical voice separation; instrument modeling; modeling of analog audio systems; audio effects.
|AUD-MIR||Music Information Retrieval and Music Language Processing
Content-based processing; discrimination; classification; structure analysis; content-based retrieval; fingerprinting; data mining; symbolic music processing; grammar-based models; music composition and improvisation; score following and music accompaniment; music annotation and metadata; symbolic music corpora.
|AUD-AUMM||Audio for Multimedia and Audio Processing Systems
Joint processing of audio and video; human-machine audio interfaces; auditory displays; distant learning; augmented and virtual reality; hardware and software systems and implementations; consumer and professional audio.
|AUD-BIO||Bioacoustics and Medical Acoustics
Human body sounds analysis; investigation of sound production and reception in animals; echo-localization.
Audio security; audio privacy; audio analysis for forensics; audio watermarking and data hiding in audio streams; acoustic event detection for forensics.
|HUMAN LANGUAGE TECHNOLOGY|
N-grams, their generalizations and smoothing methods; language model adaptation: grammar-based, structured language modelling; discriminative, maximum-entropy and feature-based language modelling; computational phonology and phonetics; dialect, accent, and idiolect at the language level;
|HLT-MTSW||Machine Translation for Spoken and Written Language
Example/phrase/syntax/semantics-based machine translafion; hybrid machine translation: word/sentence/document alignments; synchronous grammar induction; decoding: system combination; post-editing; machine transliteration and transcription; spoken language translation: speech processing for machine translation;
|HLT-UNDE||Spoken Language Understanding and Computational Semantics
Spoken language understanding; paralinguistic (emotion , age, gender, etc.), non-linguistic (gesture, sign, etc) Information processing; semantic role labell ing, multiword expressions; word sense disambiguation, representation of meaning; lexical semantics; distributional semantics; text entailment; ontology;
|HLT-DIAL||Discourse and Dialog
Learning of linguistic/discourse structure (e.g., disfluencies, sentence/topic boundanes, speech acts); co-reference and anaphora resolution; dialog management/generation/analysis; semantic analysis for discourse and dialog: intent determination: dialog act tagging;
|HLT-SDTM||Spoken Document Retrieval and Text Mining
Spoken document retrieval; linguistic pattern discovery and prediction from data; spoken term detection; named entity recognition; question answering; document summarization and generation; spoken document summanzation; information extraction and retrieval; subjectivity and sentiment analysis; text and spoken document classification; spam detection; topic detection and tracking; trend detection;
|HLT-STPA||Segmentation, Tagging, and Parsing
Morphology analysis; word segmentation; part-of-speech tagging, chunking and supertagging; models and algorithms for parsing; grammar induction; dependency parsing; multilingual parsing;
|HLT-LACL||Language Acquisition and Learning
Language acquisition, development, and learning models; computer aids for language learning; assessment of pronunciation and language fluency.
|HLT-MLMD||Machine Learning Methods
Supervised, unsupervised, semi-supervised learning; statistical methods; symbolic learning methods; biologically inspired and neural networks; reinforcement learning; active learning; online learning; deep learning; recursive and structured models, graphical and latent variable models; kernel methods; domain adaptation;
|HLT-LRES||Language Resources and Systems
Annotation and evaluation of corpora; linguistic resources development methodologies, standards, tools and evaluations; crowd-sourcing; human computer interface; assistive technology for the aged; universal access and individuals with impairments; mobile conversational interface; evaluations, systems and applications of human language technology.
Physical models of the vocal production system; bioacoustics and medical acoustics; singing and properties of the musical voice.
|SPE-SPER||Speech Perception and Psychoacoustics
Models of Speech Perception; hearing and psychoacoustics; physiological models and applications thereof; audiology applications.
Spectral and other time-frequency analysis techniques; segmental and suprasegmental analysis; distortion measures; extraction of non-linguistic information (e.g., gender, stress, etc); voice/speech disorders; speaker localization (space) (e.g., in meetings); speaker diarization (time) (e.g., in meetings); speaker clustering (e.g., in Broadcast news).
|SPE-SYNT||Speech Synthesis and Generation
Segmental-level and/or concatenative synthesis; signal processing/statistical model for synthesis; articulatory synthesis; parametric synthesis; prosody, emotional, and expressive synthesis; text-to-phoneme conversion; voice quality/morphing; audio/visual speech synthesis; multilingual synthesis; quality assessent/evaluation metrics in synthesis; tools and data for speech synthesis; text processing for speech synthesis (text normalization, syntactic and semantic analysis).
Narrow-band and wide-band speech coding; theory and techniques for signal coding (e.g., waveform, transform); modulation and source/channel coding; quantization and compression; robust coding for noisy channels; coding for Voice Over IP (VOIP); quality assessent/evaluation metrics (e.g., PESQ) in coding; new applications of VOIP.
non-noisy speech; speech enhancement for humans with hearing impairments; non-acoustic microphones for enhancement; bandwidth expansion; noise reduction.
|SPE-RECO||Acoustic Modeling for Automatic Speech Recognition
Acoustic feature extraction; low-level feature modeling - Gaussians & beyond; statistical and neural network models, deep learning models, pronunciation modeling; state clustering and novel state definitions; prosody and other speech characteristics; dialect, accent, and idiolect at the acoustic level; discriminative acoustic training methods for ASR; articulatory and physiological modeling; non-acoustic microphones for ASR; feature transformation and normalization.
|SPE-ROBU||Robust Speech Recognition
Acoustic features specifically for robust ASR (noise, channel, etc.); model/backend based robust ASR; confidence measures and rejection; speech activity/end-point detection; barge-in.
Speaker adaptation and normalization (e.g., VTLN); speaker adapted training methods; environmental/channel adaptation; idiolect adaptation; register and/or dialect adaptation.
|SPE-GASR||General Topics in Speech Recognition
Distributed Speech Recognition - Client/Server methods; alternative Statistical/Machine Learning Methods (e.g., no HMMs); word spotting; metadata (e.g., emotion, speaker, accent) extraction from acoustics; new algorithms, computational strategies, data-structures for ASR; multi-modal (such as audio-visual) speech recognition; corpora, annotation, and other resources; algorithm approximation methods in ASR; structured classification approaches.
|SPE-MULT||Multilingual Recognition and Identification
Language-type and dialect identification; multilingual speech recognition and spoken language processing; processing of non-native accents; mixed-code speech recognition and understanding; low resource and rare language processing
|SPE-LEXI||Lexical Modeling and Access
Pronunciation modeling at the lexical level; dialect, accent, and idiolect at the lexical level; multilingual aspects (e.g., unit selection); automatic lexicon learning.
|SPE-LVCR||Large Vocabulary Continuous Recognition/Search
Decoding algorithms and implementation; lattices; multi-pass strategies; miscellaneous Topics.
|SPE-SPKR||Speaker Recognition and Characterization
Features and characteristics for speaker recognition; robustness to variable and degraded channels; verification, identification, segmentation, and clustering; speaker characterization and adaptation; speaker recognition with speech recognition; speaker confidence estimation; multimodal and multimedia human speaker recognition; corpora, annotation, evaluation, and other resources; higher-level knowledge in speaker recognition.
|SPE-RCSR||Resource Constrained Speech Recognition
Low-power speech recognition; reduced computation speech recognition; ASR techniques for highly portable/mobile devices.