Search Results for author:
Found 7 papers, 0 papers with code
Incorporating Belief Function in SVM for Phoneme Recognition
The main idea of this algorithm is based on the principle of the margin maximization to find an hyperplane which separates the data into two different classes. In this paper, SVM is applied to phoneme recognition task.
The challenges of SVM optimization using Adaboost on a phoneme recognition problem
The use of digital technology is growing at a very fast pace which led to the emergence of systems based on the cognitive infocommunications.
Practical Selection of SVM Supervised Parameters with Different Feature Representations for Vowel Recognition
It is known that the classification performance of Support Vector Machine (SVM) can be conveniently affected by the different parameters of the kernel tricks and the regularization parameter, C. Thus, in this article, we propose a study in order to find the suitable kernel with which SVM may achieve good generalization performance as well as the parameters to use.
An Empirical Comparison of SVM and Some Supervised Learning Algorithms for Vowel recognition
In this article, we conduct a study on the performance of some supervised learning algorithms for vowel recognition.
A Multi Level Data Fusion Approach for Speaker Identification on Telephone Speech
Several speaker identification systems are giving good performance with clean speech but are affected by the degradations introduced by noisy audio conditions.
On the Use of Different Feature Extraction Methods for Linear and Non Linear kernels
The speech feature extraction has been a key focus in robust speech recognition research; it significantly affects the recognition performance.
Improved Frame Level Features and SVM Supervectors Approach for the Recogniton of Emotional States from Speech: Application to categorical and dimensional states
The purpose of speech emotion recognition system is to classify speakers utterances into different emotional states such as disgust, boredom, sadness, neutral and happiness.
