Preprocessing signal for Speech Emotion Recognition

Authors

DOI:

https://doi.org/10.23851/mjs.v28i3.48

Keywords:

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

Abstract

Abstract:

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

References

References:

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Published

28-07-2018

Issue

Section

Computer Science

How to Cite

[1]
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, doi: 10.23851/mjs.v28i3.48.

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