Open Access   Article Go Back

Emotion Recognition in Marathi Language by using Fast Fourier Transform

Shinde Ashok R.1 , Agnihotri Prashant P.2 , Raut S.D.3 , Khanale Prakash B.4

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-10 , Page no. 43-47, Oct-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i10.4347

Online published on Oct 31, 2019

Copyright © Shinde Ashok R., Agnihotri Prashant P., Raut S.D., Khanale Prakash B. . 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.

View this paper at   Google Scholar | DPI Digital Library

XML View
PDF Download

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: Shinde Ashok R., Agnihotri Prashant P., Raut S.D., Khanale Prakash B., “Emotion Recognition in Marathi Language by using Fast Fourier Transform,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.10, pp.43-47, 2019.

MLA Style Citation: Shinde Ashok R., Agnihotri Prashant P., Raut S.D., Khanale Prakash B. "Emotion Recognition in Marathi Language by using Fast Fourier Transform." International Journal of Computer Sciences and Engineering 7.10 (2019): 43-47.

APA Style Citation: Shinde Ashok R., Agnihotri Prashant P., Raut S.D., Khanale Prakash B., (2019). Emotion Recognition in Marathi Language by using Fast Fourier Transform. International Journal of Computer Sciences and Engineering, 7(10), 43-47.

BibTex Style Citation:
@article{R._2019,
author = {Shinde Ashok R., Agnihotri Prashant P., Raut S.D., Khanale Prakash B.},
title = {Emotion Recognition in Marathi Language by using Fast Fourier Transform},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {10 2019},
volume = {7},
Issue = {10},
month = {10},
year = {2019},
issn = {2347-2693},
pages = {43-47},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4891},
doi = {https://doi.org/10.26438/ijcse/v7i10.4347}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i10.4347}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4891
TI - Emotion Recognition in Marathi Language by using Fast Fourier Transform
T2 - International Journal of Computer Sciences and Engineering
AU - Shinde Ashok R., Agnihotri Prashant P., Raut S.D., Khanale Prakash B.
PY - 2019
DA - 2019/10/31
PB - IJCSE, Indore, INDIA
SP - 43-47
IS - 10
VL - 7
SN - 2347-2693
ER -

VIEWS PDF XML
493 520 downloads 179 downloads
  
  
           

Abstract

Emotion Recognition is a recent research area which can be applied in various applications. Speech Emotion is useful in E-learning, medical and in entertainment. The proposed work focuses on emotion recognition using Fast Fourier Transform and Marathi speech database. In this work six emotions are considered and Fast Fourier Transform is used for feature extraction and as a major feature for finding specific emotion. The Marathi words which represents the emotion like surprise and sad like Are Bapre (अरे बापरे ! ), Kiti Wilakshan (किती विलक्षण ! ), Are Deva (अरे देवा !) etc are used as a speech samples for analysis purpose. This paper highlights the overview of existing speech database as well as the newly developed Marathi emotional speech database. In this proposed work total 52 Marathi utterances are used in the experimental purpose. Fourier Transform is used to convert time domain signal into Frequency domain signal. The proposed experimental work gives 100% recognition rate for surprise and disgust emotion. Similarly 90% accuracy for sad emotion and 87.5% accuracy got for fear and angry emotion. The overall average recognition rate for six emotions is 93%. Very less accuracy rate i.e 62.5% got for happy emotion.

Key-Words / Index Term

Emotion Recognition, SER, AER

References

[1] Surabhi Vaishnav and Saurabh Mitra, “Speech Emotion Recognition: A Review”, International Journal of Engineering and Technology (IRJET), Vol. 03, Issue:04, Apr-2016.
[2] Leila Kerkeni, Youssef Serrestou, Mohamed Mbarki, Kosai Roof and Mohamed Ali Mahjoub, “Speech Emotion Recognition: Methods and Cases Study”, in Proceedings of the 10th International Conference on Agents and Artificial Intelligence (ICAART 2018) – Vol.2,Pages 175-182.
[3] Dhruvi Desai, “Emotion Recognition using Speech Signal: A Review”, International Research Journal of Engineering and Technology (IRJET), Vol. 05, Issue:04, Apr-2016.
[4] Shweta Sinha, “Analysis and Recognition of Dialects of Hindi Speech”, International Journal of Scientific Research in Computer Science and Engineering (IJSRCSE), Volume-3, Issue-5, Oct 2015.
[5] V.K. Jain and N. Tripathi, “Speech Features Analysis and Biometric Person Identification in Multilingual Environment”, International Journal of Scientific Research in Network Security and Cmmunications-6, Issue-1, February 2018.
[6] Agnihotri P.P., Shinde A.R. and Khanale P.B. “Development of Noise free Marathi Speech database using various Filtering Techniques”, Indian Journal of Research, Volume-5, Issue-2, February 2016.
[7] Oh-Wook Kwon, Kwokleung Chan, Jiucang Hao, Te-Won Lee, “Emotion Recognition by Speech Signals” EUROSPEECH 2003 - INTERSPEECH 2003 8th European Conference on Speech Communication and Technology Geneva, Switzerland, September 1-4, 2003.
[8] S.Lalitha, Sbhishek Madhavan, Bharath Bhushan, Srinivas Saketh,”Speech Emotion Recognition”, International Conference on Advances in Electronics, Computers and Communications(IJAECC), 2014.
[9] Nobuo Sato, Yasunari Obuchi, “Emotion Recognition using Mel-Frequency Cepstral Coefficients”, Journal of Natural Language Processing, pp 83-96, 2007.