Preprocessing signal for Speech Emotion Recognition




Speech, Features extraction, Emotion, Vocal, LPC, MFCC



In this paper, we introduce and study preprocessing signal for speech emotion recognition. The aim of our work is to get pure signal which is created by sampling the signal from speaker. The discrimination between speech and music waves was achieved. A good signal is obtained by using preprocessing then it used for feature extraction. The files we used in this paper are wave-type for male, female and music have sample rate 48000, bit resolution is 16-bits and Mono channel. The Berlin dataset and RAVDESS dataset are used in this work.


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Author Biography

Bashar M. Nema, Mustansiriyah University

College of Sciences,

Department of Computer Science



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How to Cite

B. M. Nema and A. A. Abdul-Kareem, “Preprocessing signal for Speech Emotion Recognition”, Al-Mustansiriyah Journal of Science, vol. 28, no. 3, pp. 157–165, Jul. 2018.



Computer Science