“2016”版本间的差异
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==Deep Learning== | ==Deep Learning== | ||
− | [[ | + | [[15.1 Network Architecture]] |
− | [[ | + | [[15.2 Optimization]] |
− | [[ | + | [[15.3 Regularization]] |
− | [[ | + | [[15.4 Sparsity]] |
− | [[ | + | [[15.5 Transfer Learning]] |
− | [[ | + | [[15.6 Sequence Learning]] |
− | [[ | + | [[15.7 Online Learning]] |
2016年2月16日 (二) 11:12的版本
目录
- 1 SPEECH PROCESS
- 1.1 Speech Perception, Production And Acquisition
- 1.2 Phonetics, Phonology, And Prosody
- 1.3 Analysis Of Paralinguistics In Speech And Language
- 1.4 Speaker And Language Identification
- 1.5 Analysis Of Speech And Audio Signals
- 1.6 Speech Coding And Enhancement
- 1.7 Speech Synthesis And Spoken Language Generation
- 1.8 Speech Recognition: Signal Processing, Acoustic Modeling, Robustness, Adaptation
- 1.9 Speech Recognition - Architecture, Search, And Linguistic Components
- 1.10 Speech Recognition - Technologies And Systems For New Applications
- 1.11 Spoken Language Processing - Dialog, Summarization, Understanding
- 1.12 Spoken Language Processing: Translation, Information Retrieval, Resources
- 1.13 Speech And Spoken-Language Based Multimodal Processing And Systems
- 2 MACHINE LEARNING
SPEECH PROCESS
Speech Perception, Production And Acquisition
1.1 Models of speech production
1.2 Physiology and neurophysiology of speech production
1.3 Neural basis of speech production
1.5 Models of speech perception
1.6 Physiology and neurophysiology of speech perception
1.7 Neural basis of speech perception
1.8 Acoustic and articulatory cues in speech perception
1.9 Interaction speech production-speech perception
1.10 Multimodal speech perception
1.11 Cognition and brain studies on speech
1.13 L1 acquisition and bilingual acquisition
1.14 L2 acquisition by children and adults
1.15 Speech and hearing disorders
1.16 Singing voice: production and perception
1.17 Speech and other biosignals
1.18 Special Session: Intelligibility under the microscope
Phonetics, Phonology, And Prosody
2.4 Discourse and dialog structures
2.7 Articulatory and acoustic features of prosody
2.9 Phonological processes and models
2.14 Phonetics of L1-L2 interaction
Analysis Of Paralinguistics In Speech And Language
3.1 Analysis of speaker states
3.2 Analysis of speaker traits
3.3 Automatic analysis of speaker states and traits
3.4 Pathological speech and language
3.7 Sentiment analysis and opinion mining
3.8 Paralinguistics in singing
3.9 Perception of paralinguistic phenomena
3.10 Phonetic and linguistic aspects of paralinguistics
Speaker And Language Identification
4.1 Language identification and verification
4.2 Dialect and accent recognition
4.3 Speaker verification and identification
4.4 Features for speaker and language recognition
4.5 Robustness to variable and degraded channels
4.6 Speaker confidence estimation
4.8 Higher-level knowledge in speaker and language recognition
4.9 Evaluation of speaker and language identification systems
4.10 Special Session: The RedDots Challenge: Towards Characterizing Speakers from Short Utterances
4.11 Special Session: The Speakers in the Wild (SITW) Speaker Recognition Challenge
Analysis Of Speech And Audio Signals
5.2 Speech analysis and representation
5.3 Audio signal analysis and representation
5.4 Speech and audio segmentation and classification
5.6 Pitch and harmonic analysis
5.7 Source separation and computational auditory scene analysis
5.8 Speaker spatial localization
5.10 Music signal processing and understanding
Speech Coding And Enhancement
6.1 Speech coding and transmission
6.2 Low-bit-rate speech coding
6.3 Perceptual audio coding of speech signals
6.4 Noise reduction for speech signals
6.5 Speech enhancement: single-channel
6.6 Speech enhancement: multi-channel
6.9 Speech enhancement in hearing aids
6.10 Adaptive beamforming for speech enhancement
6.11 Dereverberation for speech signals
6.12 Echo cancelation for speech signals
6.13 Evaluation of speech transmission, coding and enhancement
Speech Synthesis And Spoken Language Generation
7.1 Grapheme-to-phoneme conversion for synthesis
7.2 Text processing for speech synthesis
7.3 Signal processing/statistical models for synthesis
7.4 Speech synthesis paradigms and methods
7.5 Articulatory speech synthesis
7.6 Segment-level and/or concatenative synthesis
7.7 Unit selection speech synthesis
7.8 Statistical parametric speech synthesis
7.9 Prosody modeling and generation
7.10 Expression, emotion and personality generation
7.11 Synthesis of singing voices
7.12 Voice modification, conversion and morphing
7.13 Concept-to-speech conversion
7.14 Cross-lingual and multilingual aspects in speech synthesis
7.15 Avatars and talking faces
7.16 Tools and data for speech synthesis
7.17 Evaluation of speech synthesis
7.18 Special Session: Singing Synthesis Challenge: Fill-In the Gap
7.19 Special Session: Voice Conversion Challenge 2016
Speech Recognition: Signal Processing, Acoustic Modeling, Robustness, Adaptation
8.1 Feature extraction and low-level feature modeling for ASR
8.2 Prosodic features and models
8.3 Robustness against noise, reverberation
8.4 Far field and microphone array speech recognition
8.5 Speaker normalization (e.g., VTLN)
8.6 New types of neural network models and learning (e.g., new variants of DNN, CNN)
8.7 Discriminative acoustic training methods for ASR
8.8 Acoustic model adaptation (speaker, bandwidth, emotion, accent)
8.9 Speaker adaptation, speaker adapted training methods
8.10 Pronunciation variants and modeling for speech recognition
8.11 Acoustic confidence measures
8.13 Cross-lingual and multilingual aspects, non-native accents
8.14 Acoustic modeling for conversational speech (dialog, interaction)
8.15 Evaluation of speech recognition
Speech Recognition - Architecture, Search, And Linguistic Components
9.1 Lexical modeling and access: units and models
9.2 Automatic lexicon learning
9.3 Supervised/unsupervised morphological models
9.4 Prosodic features and models for language modeling
9.5 Discriminative training methods for language modeling
9.6 Language model adaptation (domain, diachronic adaptation)
9.7 Language modeling for conversational speech (dialog, interaction)
9.8 Neural networks for language modeling
9.9 Search methods, decoding algorithms, lattices, multipass strategies
9.10 New computational strategies, data-structures for ASR
9.11 Computational resource constrained speech recognition
9.13 Cross-lingual and multilingual components for speech recognition
9.14 Structured classification approaches
Speech Recognition - Technologies And Systems For New Applications
10.2 Applications in education and learning (incl. CALL, assessment of fluency)
10.3 Applications in medical practice (CIS, voice assessment, etc.)
10.4 Speech science in end-user applications
10.6 Innovative products and services based on speech technologies
10.7 Sparse, template-based representations
10.8 New paradigms (e.g. artic. models, silent speech interfaces, topic models)
10.9 Special Session: Sub-Saharan African languages: from speech fundamentals to applications
10.10 Special Session: Realism in robust speech processing
10.11 Special Session: Sharing Research and Education Resources for Understanding Speech Processing
Spoken Language Processing - Dialog, Summarization, Understanding
11.2 Multimodal human-machine interaction (conversat. agents, human-robot)
11.3 Analysis of verbal, co-verbal and nonverbal behavior
11.4 Interactive systems for speech/language training, therapy, communication aids
11.5 Stochastic modeling for dialog
11.6 Question-answering from speech
11.7 Spoken document summarization
11.8 Systems for spoken language understanding
11.9 Topic spotting and classification
11.10 Entity extraction from speech
11.11 Semantic analysis and classification
11.12 Conversation and interaction
11.13 Evaluation of speech and multimodal dialog systems
11.14 Evaluation of summarization and understanding
Spoken Language Processing: Translation, Information Retrieval, Resources
12.1 Spoken machine translation
12.2 Speech-to-speech translation systems
12.7 Spoken document retrieval
12.8 Systems for mining spoken data, search or retrieval of speech documents
12.9 Speech and multimodal resources and annotation
12.10 Metadata descriptions of speech, audio and text resources
12.11 Metadata for semantic or content markup
12.12 Metadata for ling./discourse structure (disfluencies, boundaries, speech acts)
12.13 Methodologies and tools for language resource construction and annotation
12.14 Automatic segmentation and labeling of resources
12.16 Evaluation and quality insurance of language resources
12.17 Evaluation of translation and information retrieval systems
12.18 Special Session: Open Data for Under-Resourced Languages
Speech And Spoken-Language Based Multimodal Processing And Systems
13.1 Multimodal Speech Recognition
13.3 Multimodal Speech Analysis
13.5 Multimodal Language Analysis
13.6 Multimodal and multimedia language trait recognition
13.7 Multimodal paralinguistics
13.8 Multimodal interactions, interfaces
13.9 Special Session: Auditory-visual expressive speech and gesture in humans and machines
MACHINE LEARNING
Learning Methods