Robust Acoustic Emotion Recognition Based on Cascaded Normalization and Extreme Learning Machines
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Dosyalar
Tarih
2016
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer International Publishing Ag
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
One of the challenges in speech emotion recognition is robust and speaker-independent emotion recognition. In this paper, we take a cascaded normalization approach, combining linear speaker level, non-linear value level and feature vector level normalization to minimize speaker-related effects and to maximize class separability with linear kernel classifiers. We use extreme learning machine classifiers on a four class (i.e. joy, anger, sadness, neutral) problem. We show the efficacy of our proposed method on the recently collected Turkish Emotional Speech Database.
Açıklama
13th International Symposium on Neural Networks (ISNN) -- JUL 06-08, 2016 -- Saint Petersburg, RUSSIA
Anahtar Kelimeler
Acoustic emotion recognition, Speech emotion recognition, Cascaded normalization, Extreme learning machines, ELM, Cognitive Load
Kaynak
Advances in Neural Networks - Isnn 2016
WoS Q Değeri
N/A
Scopus Q Değeri
Q3
Cilt
9719
