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==Speech Recognition - Architecture, Search, And Linguistic Components== | ==Speech Recognition - Architecture, Search, And Linguistic Components== | ||
2016年11月9日 (三) 01:01的版本
8.6 New types of neural network models and learning (e.g., new variants of DNN, CNN)
目录
- 1 Speech Recognition - Architecture, Search, And Linguistic Components
- 2 Speech Recognition - Technologies And Systems For New Applications
- 3 Spoken Language Processing - Dialog, Summarization, Understanding
- 4 Spoken Language Processing: Translation, Information Retrieval, Resources
- 5 Speech And Spoken-Language Based Multimodal Processing And Systems
- 6 MACHINE LEARNING
- 7 SPEAKER RECOGNITION
- 8 Review
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
