Open Access

An Application of Similarity Measure of Intuitionistic Fuzzy Soft Set based on Distance in Speech Emotion Recognition

Beyza Esin Özseven1*, Naim Çağman2, Turgut Özseven3
1Tokat Gaziosmanpasa University  , Tokat, Turkey
2Tokat Gaziosmanpasa University  , Tokat, Turkey
3Tokat Gaziosmanpasa University  , Tokat, Turkey
* Corresponding author: beyza_esin@hotmail.com

Presented at the 2nd International Symposium on Innovative Approaches in Scientific Studies (ISAS2018-Winter), Samsun, Turkey, Nov 30, 2018

SETSCI Conference Proceedings, 2018, 3, Page (s): 1536-1540

Published Date: 31 December 2018

In this study, we first introduced intuitionistic fuzzy soft sets and similarity measures of two intuitionistic fuzzy soft sets. We then construct a decision making method for the speech emotion recognition problem based on the similarity measure of intuitionistic fuzzy soft sets.  

Keywords - Soft sets, intuitionistic fuzzy soft sets, hamming distances, speech emotion recognition

[1] Özseven, T. (2018). Investigation of the effect of spectrogram images and different texture analysis methods on speech emotion recognition. Applied Acoustics, 142, 70-77.
[2] Majumdar, P., & Samanta, S. K. (2011). On similarity measures of fuzzy soft sets. International Journal of Advance Soft Computing and Applications, 3(2), 1-8.
[3] Çağman, N., & Deli, I. (2013). Similarity measures of intuitionistic fuzzy soft sets and their decision making. arXiv preprint arXiv:1301.0456.
[4] Liu, Z., Qin, K., & Pei, Z. (2014). Similarity measure and entropy of fuzzy soft sets. The Scientific World Journal, 2014.
[5] P. K. Maji, R. Biswas, and A. R. Roy, “Intuitionistic fuzzy soft sets,” The Journal of Fuzzy Mathematics, vol. 9, no. 3, pp. 677–692, 2001.
[6] P. K. Maji, A. R. Roy, and R. Biswas, “On intuitionistic fuzzy soft sets,” The Journal of Fuzzy Mathematics, vol. 12, no. 3, pp. 669–683, 2004.
[7] M.I. Ali, F. Feng, X. Liu, W.K. Min and M. Shabir, On some new operations in soft set theory, Computers and Mathematics with Applications, 57 (2009) 1547-1553.
[8] N. Çağman, S. Karataş and S. Enginoğlu, Soft Topology, Computers and Mathematics with Applications, 62 (2011) 351 - 358.
[9] N. Çağman and S. Enginoğlu, Soft matrices and its decision makings, Computers and Mathematics with Applications, 59 (2010) 3308-3314.
[10] N. Çağman and S. Enginoğlu, Soft set theory and uni-int decision making, European Journal of Operational Research, 207 (2010) 848-855.
[11] N. Çağman, F. Erdoğan and S. Enginoğlu, Fuzzy parameterized fuzzy soft set theory and its applications, Turkish Journal of Fuzzy Systems, 1/1, (2010) 21-35.
[12] L.A. Zadeh, Fuzzy Sets, Inform. and Control, 8 (1965) 338-353.
[13] K. Atanassov, Intuitionistic fuzzy sets, Fuzzy Sets and Systems, 20 (1986) 87-96.
[14] N. Çağman and S. Karataş, Intuitionistic fuzzy soft set theory and its decision making, Journal of Intelligent and Fuzzy Systems, DOI: 10.3233IFS2012-06015-17.
[15] K. Atanassov, Intuitionistic fuzzy sets, Theory and Applications, PhysicaVerlag, Wyrzburg, 1999.
[16] P. Majumdar and S. K. Samanta, Similarity Measure of soft sets, New Mathematics and Natural Computation,4(1) (2008) 1-12.
[17] F. Burkhardt, A. Paeschke, M. Rolfes, W. F. Sendlmeier, and B. Weiss, “A database of German emotional speech.,” in Interspeech, 2005, vol. 5, pp. 1517–1520.
[18] Özseven, T., & Düğenci, M. (2018). SPeech ACoustic (SPAC): A novel tool for speech feature extraction and classification. Applied Acoustics, 136, 1-8.

0
Citations (Crossref)
27K
Total Views
319
Total Downloads

Licence Creative Commons This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
SETSCI 2026
info@set-science.com
Copyright © 2026 SETECH
Tokat Technology Development Zone Gaziosmanpaşa University Taşlıçiftlik Campus, 60240 TOKAT-TÜRKİYE