Modeling Human Behaviors in Psychology Using Engineering Methods.

Cover -- Half Title -- Series Page -- Title Page -- Copy Right -- Contents -- Part I - Modeling Human Behaviors:An Engineering Approach -- Chapter 1 - Behavioral Signal Processing (BSP): Behavioral Informatics -- 1.1 BSP: Introduction -- 1.1.1 BSP: Technical Challenges and Complexities -- 1.2 BSP: Computational Methods for Dyadic InteractionDynamics -- 1.2.1 BSP: Further Complexities in Modeling Interaction Dynamics -- Chapter 2 - Applications in Modeling Human Behaviors Computationally -- 2.1 BSP Application Domains -- 2.2 Case Study I: Emotion Recognition from Speech -- 2.3 Case Study II: Quantifying Implicit Vocal Entrainment inHuman Interactions -- 2.4 Case Study III: Data-driven Perceptual Experiment -- Part II - Affective Computing fromSpeech -- Chapter 3 - Individual Utterance Emotion Recognition -- 3.1 Introduction -- 3.2 Emotion Databases and Acoustic Feature Extraction -- 3.2.1 The AIBO Database -- 3.2.2 The USC IEMOCAP Database -- 3.2.3 Acoustic Feature Extraction -- 3.2.4 Feature Selection and Normalization -- 3.3 Emotion Classification Framework -- 3.3.1 Building the Hierarchical Decision Tree -- 3.3.2 Building the Hierarchical Decision Tree for the AIBO Database andthe USC IEMOCAP Database -- 3.3.3 Classifier for Binary Classification Tasks -- 3.3.3.1 Bayesian Logistic Regression -- 3.4 Emotion Recognition Experiment Setup and Results -- 3.4.1 The AIBO Database -- 3.4.1.1 Results of Experiment I on the AIBO database -- 3.4.1.2 Results of Experiment II on the AIBO database -- 3.4.2 The USC IEMOCAP Database -- 3.4.2.1 Experiment Result of the USC IEMOCAP Database -- 3.5 Conclusions and Future Work -- Chapter 4 - Dialog-based Emotion Recognition -- 4.1 Introduction -- 4.2 Emotion Database and Annotation -- 4.2.1 The USC IEMOCAP Database -- 4.2.2 Emotion Annotation -- 4.3 Dynamic Bayesian Network Model.

4.4 Experimental Results and Discussion -- 4.4.1 Acoustic Feature Extraction -- 4.4.2 Experiment Setup -- 4.4.3 Experiment Results and Discussion -- 4.5 Conclusions and Future Work -- Part III Quantifying Human Behavior in Psychology -- Chaper 5 - Implicit Vocal Synchrony Quantification -- 5.1 Introduction -- 5.2 BSP Database: The Couple Therapy Corpus -- 5.2.1 Pre-processing and Audio Feature Extraction -- 5.2.2 Behavioral Codes of Interest -- 5.3 Signal-derived Vocal Entrainment Quantification -- 5.3.1 PCA-based Similarity Measures -- 5.3.1.1 Symmetric Similarity Measures -- 5.3.1.2 Directional Similarity Measures -- 5.3.2 Representative Vocal Features -- 5.3.3 Vocal Entrainment Measures in Dialogs -- 5.4 Analysis of Vocal Entrainment Measures -- 5.4.1 Natural Cohesiveness of Dialogs -- 5.4.2 Entrainment in Affective Interactions -- 5.5 Affect Classification using Entrainment Measures -- 5.5.1 Classification Framework -- 5.5.1.1 Factorial Hidden Markov Model -- 5.5.2 Classification Setup -- 5.5.3 Classification Results and Discussions -- 5.6 Conclusions and Future Work -- Chapter 6 - Analysis of Vocal Synchrony in Couples Therapy -- 6.1 Introduction -- 6.2 BSP Database: The Couple Therapy Corpus -- 6.3 PCA-based Vocal Entrainment Measures -- 6.3.1 Symmetric Entrainment Measures -- 6.3.2 Directional Entrainment Measures -- 6.3.2.1 Acoustic Features -- 6.3.3 Canonical Correlation Analysis -- 6.4 Analysis of Results and Discussions -- 6.4.1 Correlation Analysis: The Four Behavioral Dimensions -- 6.4.2 Canonical Correlation Analysis: Withdrawal -- 6.5 Lessons Learnt from Correlation Analysis -- 6.6 Vocal Entrainment and Demand-and-Withdraw in CoupleConflict -- 6.6.1 Demand and Withdraw -- 6.6.2 Behavioral Influence and Polarization of Demand and Withdraw -- 6.6.3 Data Analysis -- 6.6.4 Results and Discussions.

Part IV Data-driven Perceptual Experiment -- Chapter 7 - Multiple Instance Learning Framework for Perceptual Experiment -- 7.1 Introduction -- 7.2 BSP Database: The Couple Therapy Corpus -- 7.3 Computational Framework -- 7.3.1 Multiple Instance Learning -- 7.3.2 Sequential Probability Ratio Test -- 7.4 Analysis Setup -- 7.4.1 Lexical Feature Extraction -- 7.4.2 Classification Setup -- 7.5 Detection Results and Discussions -- 7.6 Isolated-Saliency vs. Causal-Integration -- 7.7 Conclusions and Future Work -- Part V Outlook of BSP -- Chapter 8 - Continuously Emerging Importance of Modeling Human Behavior -- Bibliography -- Author Biography.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.