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Application of fuzzy C-means clustering algorithm to spectral features for emotion classification from speech

Neural Computing and Applications · Nisan 2018

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YÖKSİS Kayıtları
Application of fuzzy C-means clustering algorithm to spectral features for emotion classification from speech
Neural Computing and Applications · 2018 SCI-Expanded
Prof. Dr. HUMAR KAHRAMANLI ÖRNEK →
Application of fuzzy C-means clustering algorithm to spectral features for emotion classification from speech
Neural Computing and Applications SCI-Expanded
Prof. Dr. HUMAR KAHRAMANLI ÖRNEK →
YÖKSİS ISSN Eşleşmesi

Bu dergide (ISSN eşleşmesi) kurumun 20 kaydı bulundu.

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Application of fuzzy C-means clustering algorithm to spectral features for emotion classification from speech
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Makale Bilgileri

Dergi Neural Computing and Applications
ISSN09410643
Yayın TarihiNisan 2018
Cilt / Sayfa29 · 59-66
DOI10.1007/s00521-016-2712-y
Scopus ID2-s2.0-84996868118
Özet In the present study, emotion recognition from speech signals was performed by using the fuzzy C-means algorithm. Spectral features obtained from speech signals were used as features. The spectral features used were Mel frequency cepstral coefficients and linear prediction coefficients. Certain statistical features were extracted from the spectral features obtained in the study. After the selection of the extracted features, cluster centers were identified by using type-1 fuzzy C-means (FCM) algorithm and used as input to the classifier. Supervised classifiers such as ANN, NB, kNN, and SVM were used for classification. In the study, all seven emotions of the EmoDB database were used. Of the features obtained, FCM clustering was applied to Mel coefficients and obtained clusters centers were used as input for classification. The results showed that using FCM for preprocessing aim increased the success rate. The comparison of the classification methods showed that the maximum success rate was obtained as 92.86% using the SVM classifier.

Yazarlar (2)

1
Semiye Demircan
2
Humar Kahramanli

Anahtar Kelimeler

Emotion recognition Fuzzy C-means LPC MFCC

Kurumlar

Selçuk Üniversitesi
Selçuklu Turkey
Scimago Dergi (ISSN Eşleşmesi)
Neural Computing and Applications
Q1
SJR Skoru1,102
H-Index146
YayıncıSpringer London
ÜlkeUnited Kingdom
Artificial Intelligence (Q1)
Software (Q1)
Dergi sayfasına git

Metrikler

51
Atıf
2
Yazar
4
Anahtar Kelime

Sistemimizdeki Yazarlar

HK
HUMAR KAHRAMANLI ÖRNEK
Prof. Dr.

Hızlı Erişim

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