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Recognition of Human Emotion by Speech Processing

R.D. Bodke1 , M.P. Satone2

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-10 , Page no. 261-264, Oct-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i10.261264

Online published on Oct 31, 2018

Copyright © R.D. Bodke, M.P. Satone . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: R.D. Bodke, M.P. Satone, “Recognition of Human Emotion by Speech Processing,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.10, pp.261-264, 2018.

MLA Style Citation: R.D. Bodke, M.P. Satone "Recognition of Human Emotion by Speech Processing." International Journal of Computer Sciences and Engineering 6.10 (2018): 261-264.

APA Style Citation: R.D. Bodke, M.P. Satone, (2018). Recognition of Human Emotion by Speech Processing. International Journal of Computer Sciences and Engineering, 6(10), 261-264.

BibTex Style Citation:
@article{Bodke_2018,
author = {R.D. Bodke, M.P. Satone},
title = {Recognition of Human Emotion by Speech Processing},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {10 2018},
volume = {6},
Issue = {10},
month = {10},
year = {2018},
issn = {2347-2693},
pages = {261-264},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3015},
doi = {https://doi.org/10.26438/ijcse/v6i10.261264}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i10.261264}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3015
TI - Recognition of Human Emotion by Speech Processing
T2 - International Journal of Computer Sciences and Engineering
AU - R.D. Bodke, M.P. Satone
PY - 2018
DA - 2018/10/31
PB - IJCSE, Indore, INDIA
SP - 261-264
IS - 10
VL - 6
SN - 2347-2693
ER -

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Abstract

The emotion recognition from speech is used for in human computer interaction. Most of researchers doing research on emotion recognition using speech signal. This project attempts language emotion recognition using speech signal of English language. The emotional speech samples are stored in database and used for Training And Testing. The feature extraction MFCC, PSD and Pitch detection algorithms are used. For classification of different emotions like Angry, Happy/Joy and Normal state SVM classifier is used. The all steps are implemented using MATLAB software. Raspberry pi is used for detection of emotion on hardware This classified emotions can be used for various application areas like medical, security, military etc.

Key-Words / Index Term

MFCC, PSD, SVM etc

References

[1] Moataz El Ayadi, Mohamed S. Kamel,Fakhri Karray, “Survey on speech emotio n recognition: Features, classification schemes and databases” , W aterloo, Ontario, Canada,july 2011, , Pages 572-587.
[2] http://cs229.stanford.edu/proj2007/ShahHewlett%20
[3] Surekha Reddy Bandela, T. Kishore Kumar “Stressed Speech Emotion Recognition using feature fusion of Teager Energy Operator and MFCC,”IEEE 2017.
[4] Jeet Kumar, Om Prakash Prabhakar , Navneet Kumar Sahu,” Comparative Analysis of Different Feature Extraction and Classifier Techniques for Speaker Identification Systems: A Review”, IJIRCCE 2014.
[5] Sreeram Ganji, Rohit Sinha,“ Exploring Recurrent Neural Network based Acoustic and Linguistic Modeling for Children’s Speech Recognition”, IEEE Region 10 Conference (TENCON), Malaysia, November 5-8, 2017.
[6] Namrata Dave, “Feature Extraction Methods LPC, PLP and MFCC In Speech Recognition,” Ieee International Journal For Advance Research In Engineering And Technology, July 2013.
[7] Dr.V.AjanthaDevi,Ms.V.Suganya,” An Analysis on Types of Speech RecognitionandAlgorithms,”IJCST,April2016.
[8] Pavol Harár1, Radim Burget1 and Malay Kishore Dutta,” Speech Emotion Recognition with Deep Learning,” 2017 4th International Conference on Signal Processing and Integrated Networks.
[9] Markus Niermann, Peter Jax, Peter Vary,” Joint Near-End Listening Enhancement And Far-End Noise Reduction,” 2017 Ieee.
[10] Amritha Vijayan, Bipil Mary Mathai, Karthik Valsalan, Riyanka Raji Johnson, Lani Rachel Mathew,” Throat Microphone Speech Recognition using MFCC,” International Conference on Networks & Advances in Computational Technologies, 2017.
[11] Pooja A, Pravena D, Govind D,” Significance of Exploring Pitch only Features for the Recognition of Spontaneous Emotions from Speech Signals,”IEEE 2017.
[12] D.S.Shete, Prof. S.B. Patil, Prof. S.B. Patil,” Zero crossing rate and Energy of the Speech Signal of Devanagari Script,” IOSR Journal of VLSI and Signal Processing, Jan 2014.
[13] Mohan Ghai, Shamit Lal, Shivam Dugga l and Shrey Manik,” Emotion Recognition On Speech Signals Using Machine Learning,”IEEE2017.