1.

Record Nr.

UNINA9910734829703321

Autore

Cabada Ramón Zatarain

Titolo

Multimodal Affective Computing : Technologies and Applications in Learning Environments / / by Ramón Zatarain Cabada, Héctor Manuel Cárdenas López, Hugo Jair Escalante

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023

ISBN

3-031-32542-7

Edizione

[1st ed. 2023.]

Descrizione fisica

1 online resource (211 pages)

Altri autori (Persone)

LópezHéctor Manuel Cárdenas

EscalanteHugo Jair

Disciplina

371.334

Soggetti

Machine learning

Learning, Psychology of

Pattern recognition systems

User interfaces (Computer systems)

Human-computer interaction

Machine Learning

Learning Theory

Automated Pattern Recognition

User Interfaces and Human Computer Interaction

Aprenentatge automàtic

Interacció persona-ordinador

Interfícies d'usuari (Sistemes d'ordinadors)

Llibres electrònics

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

Part I: Fundamentals -- Chapter 1. Affective Computing -- Chapter 2. Machine learning and pattern recognition in affective computing -- Chapter 3. Affective Learning Environments -- Part II: Sentiment Analysis for Learning Environments -- Chapter 4. Building resources for sentiment detection -- Chapter 5. Methods for data representation -- Chapter 6. Designing and testing the classification models -- Chapter 7. Model integration to a learning system -- Part III:



Multimodal Recognition of Learning-Oriented Emotions -- Chapter 8. Building Resources for Emotion Detection -- Chapter 9. Methods for Data Representation -- Chapter 10. Multimodal recognition systems -- Chapter 11. Multimodal emotion recognition in learning environments -- Part IV: Automatic Personality Recognition -- Chapter 12. Building resources for personality recognition -- Chapter 13. Methods for data representation -- Chapter 14. Personality recognition models -- Chapter 15. Multimodal personality recognition for affective computing.

Sommario/riassunto

This book explores AI methodologies for the implementation of affective states in intelligent learning environments. Divided into four parts, Multimodal Affective Computing: Technologies and Applications in Learning Environments begins with an overview of Affective Computing and Intelligent Learning Environments, from their fundamentals and essential theoretical support up to their fusion and some successful practical applications. The basic concepts of Affective Computing, Machine Learning, and Pattern Recognition in Affective Computing, and Affective Learning Environments are presented in a comprehensive and easy-to-read manner. In the second part, a review on the emerging field of Sentiment Analysis for Learning Environments is introduced, including a systematic descriptive tour through topics such as building resources for sentiment detection, methods for data representation, designing and testing the classification models, and model integration into a learning system. The methodologies corresponding to Multimodal Recognition of Learning-Oriented Emotions are presented in the third part of the book, where topics such as building resources for emotion detection, methods for data representation, multimodal recognition systems, and multimodal emotion recognition in learning environments are presented. The fourth and last part of the book is devoted to a wide application field of the combination of methodologies, such as Automatic Personality Recognition, dealing with issues such as building resources for personality recognition, methods for data representation, personality recognition models, and multimodal personality recognition for affective computing. This book can be very useful not only for beginners who are interested in affective computing and intelligent learning environments, but also for advanced and experts in the practice and developments of the field. It complies an end-to-end treatment on these subjects, especially with educational applications, making it easy for researchers and students to get on track with fundamentals, established methodologies, conventional evaluation protocols, and the latest progress on these subjects.