Preprocessing signal for Speech Emotion Recognition
DOI:
https://doi.org/10.23851/mjs.v28i3.48Keywords:
Speech, Features extraction, Emotion, Vocal, LPC, MFCCAbstract
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.Downloads
References
References:
S.U.Mehmet et al , "A Comparison of Neural Networks for Real Time Emotion Recognition from speech signal " , Wseas transactions on signal processing , Vol. 5 , No. 3 , PP. 116-125 , 2009 .
A. S. Utane and S.L. Nalbalwar, “Emotion Recognition through Speech” , International Journal of Applied Information Systems (IJAIS) , 2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET ) , pp.5-8, 2013.
S. P. Robbins and T. A. Judge , “Organizational Behavior” , Manufactured in the United States of America , 15th edition , 2013 .
K. S. Rao et al , “Emotion Recognition from Speech” , International Journal of Computer Science and Information Technologies, Vol. 3, No.2 ,pp.3603-3607 , 2012.
D. Kim and B.C. Kim , “Speech Recognition using Hidden Markov Models in Embedded Platform” , Indian Journal of Science and Technology, Vol 8(34), 2015.
B.SUJATHA and O. AMEENA , “Speech Emotion Recognition Using HMM, GMM and SVM Models” , International Journal of Professional Engineering Studies , Volume VI /Issue 3 , pp.311-318, 2016 .
R.D.Shah and Dr. A..C.Suthar , “Speech Emotion Recognition Based on SVM Using MATLAB” , International Journal of Innovative Research in Computer and Communication Engineering , Vol. 4, Issue 3, pp. 2916-2921, 2016 .
N. N. Nisha and P. C. Latane , " Real Time Speaker Recognition using Mel- Frequency Cepstral Coefficients (MFCC) ,VQLBG & GMM Techniques " , International Journal of Innovative Research in Science, Engineering and Technology , Vol. 5, Issue 6, pp. 9923 - 9930 , 2016 .
Yahya A.Mohammed , " Speaker Identification Using MFCC and VQ", MSC thesis , University of Al-Mustasiriyah , College of Science , Computer Department , 2016.
T. F. Quatieri , “Discrete-Time Speech Signal Processing: Principles and Practice”, first edition , 2001.
DOUGLAS O’SHAUGHNESSY, "Interacting With Computers by Voice: Automatic Speech Recognition and Synthesis", IEEE, Volume: 91, Pages: 1273- 1305, NO: 9, 2003
Antonio M. Peinado, Jose C.Segura, "Speech recognition over digital channels ", John Wiley & Sons Ltd, 2006.
Homayoon Beigi, "Fundamentals of Speaker Recognition", Springer Science, 2011.
V. Radha, C. Vimala, M. Krishnaveni, "Isolated Word Recognition System Using Back Propagation Network for Tamil Spoken Language", Springer-Verlag Berlin Heidelberg, p: 254-264, 2011.
S. Deviant MAT, " practically cheating statistics handbook", 2011.
Downloads
Key Dates
Published
Issue
Section
License
(Starting May 5, 2024) Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution (CC-BY) 4.0 License that allows others to share the work with an acknowledgement of the work’s authorship and initial publication in this journal.