Publication Type : Conference Paper
Publisher : 2017 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2017
Source : 2017 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2017, Institute of Electrical and Electronics Engineers Inc. (2018)
ISBN : 9781509066209
Keywords : Artificial intelligence, Auto encoders, Cross-corpus technique, Domain Adaptation, Learning systems, personality, Psychological state
Campus : Bengaluru
School : School of Engineering
Department : Electronics and Communication
Year : 2018
Abstract : pThe 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. © 2017 IEEE./p
Cite this Research Publication : N. Vijay, Tripathi, S., and Lalitha, S., “Personality Traits from Speech Signal Using Cross-Corpus Technique”, in 2017 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2017, 2018.