SVM based Emotional Speaker Recognition using MFCC-SDC Features
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2017, Vol 8, Issue 4
Abstract
Enhancing the performance of emotional speaker recognition process has witnessed an increasing interest in the last years. This paper highlights a methodology for speaker recognition under different emotional states based on the mul-ticlass Support Vector Machine (SVM) classifier. We compare two feature extraction methods which are used to represent emotional speech utterances in order to obtain best accuracies. The first method known as traditional Mel-Frequency Cepstral Coefficients (MFCC) and the second one is MFCC combined with Shifted-Delta-Cepstra (MFCC-SDC). Experimentations are conducted on IEMOCAP database using two multiclass SVM ap-proaches: One-Against-One (OAO) and One Against-All (OAA). Obtained results show that MFCC-SDC features outperform the conventional MFCC.
Authors and Affiliations
Asma Mansour, Zied Lachiri
Keywords
Related Articles
- EP ID EP258416
- DOI 10.14569/IJACSA.2017.080471
- Views 97
- Downloads 0
ETEEM- Extended Traffic Aware Energy Efficient MAC Scheme for WSNs
Idle listening issue arises when a sensor node listens to medium despite the absence of data which results in consumption of energy. ETEEM is a variant of Traffic Aware Energy Efficient MAC protocol (TEEM) which focuses...
A New Image-Based Model For Predicting Cracks In Sewer Pipes
Visual inspection by a human operator has been mostly used up till now to detect cracks in sewer pipes. In this paper, we address the problem of automated detection of such cracks. We propose a model which detects crack...
A Novel Energy Efficient Mobility Aware MAC Protocol for Wireless Sensor Networks
Dealing with mobility at the link layer in an efficient and effective way is a formidable challenge in Wireless Sensor Networks due to recent boom in mobile applications and complex network scenarios. Most of the current...
Modelling for Forest Fire Evolution Based on the Energy Accumulation and Release
Forest fire evolution plays an important role in the decision-making of controlling the forest fire. This paper aims to simulate the dynamics of the forest fire spread using a cellular automaton approach. Having analyzed...
Diagnosis of Diabetes by Applying Data Mining Classification Techniques
Health care data are often huge, complex and heterogeneous because it contains different variable types and missing values as well. Nowadays, knowledge from such data is a necessity. Data mining can be utilized to extrac...