Affective computing
Bimodal expression of emotion by face and voice
MULTIMEDIA '98 Proceedings of the sixth ACM international conference on Multimedia: Face/gesture recognition and their applications
Data mining: concepts and techniques
Data mining: concepts and techniques
Transition network grammars for natural language analysis
Communications of the ACM
Toward Machine Emotional Intelligence: Analysis of Affective Physiological State
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
Emotion Detection from Speech to Enrich Multimedia Content
PCM '01 Proceedings of the Second IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
An emotion processing system based on fuzzy inference and subjective observations
ANNES '95 Proceedings of the 2nd New Zealand Two-Stream International Conference on Artificial Neural Networks and Expert Systems
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Statistical Models for Co-occurrence Data
Statistical Models for Co-occurrence Data
Emotional Chinese talking head system
Proceedings of the 6th international conference on Multimodal interfaces
Emotion detection in task-oriented spoken dialogues
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 3 (ICME '03) - Volume 03
Affect analysis of text using fuzzy semantic typing
IEEE Transactions on Fuzzy Systems
Symbolic connectionism in natural language disambiguation
IEEE Transactions on Neural Networks
Building emotion lexicon from weblog corpora
ACL '07 Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions
DocEmoX: A System for the Typography-Derived Emotional Annotation of Documents
UAHCI '09 Proceedings of the 5th International Conference on Universal Access in Human-Computer Interaction. Part III: Applications and Services
Automatic event-level textual emotion sensing using mutual action histogram between entities
Expert Systems with Applications: An International Journal
Journal of Biomedical Informatics
Modeling reader's emotional state response on document's typographic elements
Advances in Human-Computer Interaction
ACII'11 Proceedings of the 4th international conference on Affective computing and intelligent interaction - Volume Part I
A regression approach to affective rating of chinese words from ANEW
ACII'11 Proceedings of the 4th international conference on Affective computing and intelligent interaction - Volume Part II
Emotion recognition from speech: a review
International Journal of Speech Technology
Event-Level textual emotion sensing based on common action distributions between event participants
IEA/AIE'12 Proceedings of the 25th international conference on Industrial Engineering and Other Applications of Applied Intelligent Systems: advanced research in applied artificial intelligence
Proceedings of the 21st ACM international conference on Information and knowledge management
A high-order hidden Markov model for emotion detection from textual data
PKAW'12 Proceedings of the 12th Pacific Rim conference on Knowledge Management and Acquisition for Intelligent Systems
Exploiting Psychological Factors for Interaction Style Recognition in Spoken Conversation
IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
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This study presents a novel approach to automatic emotion recognition from text. First, emotion generation rules (EGRs) are manually deduced from psychology to represent the conditions for generating emotion. Based on the EGRs, the emotional state of each sentence can be represented as a sequence of semantic labels (SLs) and attributes (ATTs); SLs are defined as the domain-independent features, while ATTs are domain-dependent. The emotion association rules (EARs) represented by SLs and ATTs for each emotion are automatically derived from the sentences in an emotional text corpus using the a priori algorithm. Finally, a separable mixture model (SMM) is adopted to estimate the similarity between an input sentence and the EARs of each emotional state. Since some features defined in this approach are domain-dependent, a dialog system focusing on the students' daily expressions is constructed, and only three emotional states, happy, unhappy, and neutral, are considered for performance evaluation. According to the results of the experiments, given the domain corpus, the proposed approach is promising, and easily ported into other domains.