Improved Speaker-Independent Emotion Recognition from Speech Using Two-Stage Feature Reduction

Authors

  • Hasrul Mohd Nazid School of Mechatronic Engineering, Universiti Malaysia Perlis, Malaysia
  • Hariharan Muthusamy School of Mechatronic Engineering, Universiti Malaysia Perlis, Malaysia
  • Vikneswaran Vijean School of Mechatronic Engineering, Universiti Malaysia Perlis, Malaysia
  • Sazali Yaacob Kulim Hi-Tech Park, Malaysia

DOI:

https://doi.org/10.32890/jict2015.14.4

Keywords:

Emotional speech, cepstral features, feature reduction, emotion recognition

Abstract

In the recent years, researchers are focusing to improve the accuracy of speech emotion recognition. Generally, high emotion recognition accuracies were obtained for two-class emotion recognition, but multi-class emotion recognition is still a challenging task . The main aim of this work is to propose a two-stage feature reduction using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) for improving the accuracy of the speech emotion recognition (ER) system. Short-term speech features were extracted from the emotional speech signals. Experiments were carried out using four different supervised classifi ers with two different emotional speech databases. From the experimental results, it can be inferred that the proposed method provides better accuracies of 87.48% for speaker dependent (SD) and gender dependent (GD) ER experiment, 85.15% for speaker independent (SI) ER experiment, and 87.09% for gender independent (GI) experiment.

 

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Published

28-04-2015

Issue

Vol. 14 (2015): Journal of Information and Communication Technology (JICT) Vol. 14, 2015

Section

Articles

How to Cite

Mohd Nazid, H., Muthusamy, H., Vijean, V., & Yaacob, S. (2015). Improved Speaker-Independent Emotion Recognition from Speech Using Two-Stage Feature Reduction. Journal of Information and Communication Technology, 14, 57-76. https://doi.org/10.32890/jict2015.14.4

Research impact

Harvested 2026-09-06
13 citations, from OpenAlex — the highest of the sources checked

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Identifiers DOI 10.32890/jict2015.14.4 OpenAlex W4255005081 Scopus 85182138125

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