Computational Modeling of Emotions and Affect in Social-Cultural Interaction

Abstract

The objective of this proposal was to develop computational models for emotion recognition in speech and study various impacting factors including social, cultural, and language effect on such models. Accomplishments in the project are the following. First, emotion recognition performance was improved upon the state-of-the-art. Different methods were developed to improve model performance, including employing sub-sentence units, advanced feature transform, deep learning, and more features from acoustic and textual information sources. Second, a cross-lingual study was performed that shed light on how human perception and automatic recognition of emotion differs and how performance in cross-lingual setups varies. This project supported several students, leading partly to one Ph.D dissertation

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Document Details

Document Type
Technical Report
Publication Date
Oct 02, 2013
Accession Number
ADA591829

Entities

People

  • Yang Liu

Organizations

  • University of Texas at Dallas

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Automated Speech Recognition
  • Automatic
  • Classification
  • Computational Modeling
  • Computer Languages
  • Deep Learning
  • Dimensionality Reduction
  • Language
  • Learning
  • Machine Learning
  • Perception
  • Recognition
  • Signal Processing
  • Students
  • Supervised Machine Learning

Readers

  • Computational Linguistics
  • Computational Modeling and Simulation
  • Speech Processing/Speech Recognition.

Technology Areas

  • AI & ML
  • AI & ML - Machine Translation