Personality Traits from Speech Signal using Cross- Corpus Technique
|Title||Personality Traits from Speech Signal using Cross- Corpus Technique|
|Publication Type||Conference Proceedings|
|Year of Conference||2018|
|Authors||Vijay, N., S.. Tripathi, and S.. Lalitha|
|Conference Name||IEEE International Conference on Computational Intelligence and Computing Research|
|Keywords||Dept. of Electronics and communication Engineering.|
The focus of this work is to detect the psychological emotional state of a human and also determine the personality trait of the person using speech samples. Cross-corpus technique has been employed for validation. Various Spectral features of speech along with Domain-Adaptive Least square Regression (DaLSR) and Auto-encoder classifier are considered. Voice samples from the publicly available database of Berlin and Enterface are used. The work is extended to classify the personality of a person into introvert or extrovert using detected psychological state. Using cross-corpus technique an improvement of 15% is obtained for psychological state classification compared to the existing reported work. The technique of personality classification is an initial attempt and needs to be improved for better recognition.