Indian Journal of Public Health Research & Development
  • Year: 2018
  • Volume: 9
  • Issue: 9

Stress speech recognition using support vector machine and random forest

1Assistant Professor, Dept. of Electronics and Communication, Silicon Institute of Technology, Bhubaneswar, Odisha

2Dept. of Electronics and Communication, Silicon Institute of Technology, Bhubaneswar, Odisha

3Professor, School of Electronics Engineering, KIIT University, Bhubaneswar, Odisha, India

Online published on 16 October, 2018.

Abstract

The Purpose of the study stress speech analysis using support vector machine and random forest algorithms and also compare the performance of the two methods for efficient stress speech recognition. The reason for the development and improvement of speech stress recognition systems is wide usability in nowadays automatic voice controlled systems.

This study uses a database of 200 different speech samples collected randomly from different individuals for the same sentence, “The weather is too hot today.” We get training dataset and test dataset which helps in the analysis of the signal in accordance with both the algorithms.

The efficiency of Support Vector Machine and Random Forest in stress speech recognition.

Extremely useful in healthcare centers, Psychiatry treatment centers and helpful for psychological improvement of individuals

Keywords

Speech signal, Support Vector Machine (SVM), Random Forest(RF)