1. Speech Analysis (SPE-ANLS)
  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)

2. Speech Enhancement (SPE-ENHA)
  Control and reduction of channel noise (e.g., reverb, room response)
  Perceptual enhancement of non-noisy speech
  Speech enhancement for humans with hearing impairments
  Non-acoustic microphones for enhancement
  Bandwidth expansion
  Noise Reduction

3. Acoustic Modeling for Automatic Speech Recognition (SPE-RECO)
  Feature Extraction
  Low-level feature modeling - Gaussians & beyond
  Pronunciation modeling at the acoustic level
  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
  Feature Transformation and Normalization

4. Robust Speech Recognition (SPE-ROBU)
  Features specifically for robust ASR (noise, channel, etc)
  Model/backend based robust ASR
  Confidence measures and rejection
  Speech Activity/End-point detection
  Barge-in
  Non-acoustic microphones for ASR

5. Speech Adaptation/Normalization (SPE-ADAP)
  Speaker adaptation and normalization (e.g., VTLN)
  Speaker adapted training methods
  Environmental/Channel adaptation
  Idiolect adaptation
  Register and/or dialect adaptation

6. General Topics in Speech Recognition (SPE-GASR)
 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

7. Multilingual Recognition and Identification (SPE-MULT)
 Language (LID) and dialect (DID) identification
 Multilingual Speech recognition
 Processing of non-native accents

8. Lexical Modeling and Access (SPE-LEXI)
 Pronunciation modeling at the lexical level
 Dialect, accent, and idiolect at the lexical level
 Multilingual aspects (e.g., unit selection)
 Automatic lexicon learning

9. Large Vocabulary Continuous Recognition/Search (SPE-LVCR)
 Decoding algorithms and implementation
 Lattices
 Multi-pass strategies
 Miscellaneous Topics

10. Speaker Recognition and Characterization (SPE-SPKR)
 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

11. Resource constrained speech recognition (SPE-RCSR)
 Low-power speech recognition
 Reduced computation speech recognition
 ASR techniques for highly portable/mobile devices

12. Spoken Language Understanding (SLP-UNDE)
 Paralinguistic (emotion, age, gender, rate, etc.) information
 Nonlinguistic (meaning external to language) information, gestures, etc.
 Semantic classification
 Question/answering from speech
 Entity extraction from speech
 Spoken document summarization
 Detecting linguistic/discourse structure (e.g., disfluencies, sentence/topic boundaries, speech acts)
 Relation to and interpretation of sign language

13. Human Spoken Language Acquisition, Development and Learning (SLP-LADL)
 Language acquisition, development, and learning models
 Computer aids for language learning
 Attributes and modeling techniques for assessment of language fluency

14. Spoken and Multimodal Dialog Systems and Applications (SLP-SMMD)
 Spoken and multimodal dialog systems, applications, and architectures
 Stochastic Learning for dialog modeling
 Response Generation
 Technologies for the aged
 Evaluation metrics and standards
 Speech/voice-based human-computer interfaces (HCI)
 Speech HCI for individuals with impairments (blindness, etc.) and universal access (UA)
 other applications

15. Speech data mining and Document Retrieval (SLP-SMIR)
 Analysis and Evaluations for mining spoken data
 Search/retrieval of speech documents
 Mining heterogeneous speech and multimedia data
 Speech data mining theory, algorithms, and methods
 Core machine learning algorithms for data mining
 Topic spotting and classification
 Pattern discovery and prediction from data
 Applications and tools for speech data mining

16. Machine Translation of Speech (SLP-SSMT)
 Semi-automatic and data driven methods
 Speech processing for MTS
 Corpora, annotation, and other resources
 Interlingua and transfer approaches
 Integration of speech and linguistic processing
 Machine transliteration for named entities
 Evaluation metrics (e.g., BLEU)
 Systems and applications for MTS

17. Language Modeling, for Speech and SLP (SLP-LANG)
 N-grams, their generalizations and smoothing methods.
 Language Model Adaptation
 Grammar based language modeling
 Maxent and feature based language modeling
 Dialect, accent, and idiolect at the language level
 Discriminative LM Training Methods
 Other approaches to LMs
 Structured classification approaches

18. Spoken language resources and annotation (SLP-REAN)
 General corpora, annotation, and other resources

19. Other Applications of Speech Recognition and Understanding