Innovative Automatic Discrimination Multimedia Documents for Indexing using Hybrid GMM-SVM Method
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2019, Vol 10, Issue 1
Abstract
In this paper, a new parameterization method sound discrimination of multimedia documents based on entropy phase is presented to facilitate indexing audio documents and speed up their searches in digital libraries or the retrieval of audio documents in the network, to detect speakers in purely judicial purposes and translate films into a specific language. There are four procedures of an indexing method are developed to solve these problems which are based on (parameterization, training, modeling and classification). In first step new temporal characteristics and descriptors are extracted. However, the GMM and SVM classifiers are associated with the other procedures. The MATLAB environment is the basis of the simulation of the proposed algorithm whose system performance is evaluated from a database consisting of music containing several segments of speech.
Authors and Affiliations
Debabi Turkia, Bousselmi Souha, Cherif Adnen
Location Prediction in a Smart Environment
The context prediction and especially the location prediction is an important feature for improving the performance of smart systems. Predicting the next location or context of the user make the system proactive, so the...
A Qualitative Comparison of NoSQL Data Stores
Due to the proliferation of big data with large volume, velocity, complexity, and distribution among remote servers, it became obvious that traditional relational databases are unsuitable for meeting the requirements of...
Global Citation Impact rather than Citation Count
The progressing bloom in the tome of scientific literature available today debars researchers from efficiently shrewd the relevant from irrelevant content. Researchers are persistently engrossed in impactful papers, auth...
A Classification Model for Imbalanced Medical Data based on PCA and Farther Distance based Synthetic Minority Oversampling Technique
Medical data are extensively used in the diagnosis of human health. So it has played a vital role for physicians as well as in medical engineering. Accordingly, many types of research are going on related to this to have...
Prediction by a Hybrid of Wavelet Transform and Long-Short-Term-Memory Neural Network
Data originating from some specific fields, for in-stance tourist arrivals, may exhibit a high degree of fluctuations as well as non-linear characteristics due to time varying behaviors. This paper proposes a new hybrid...