PROJECT TITLE :

Speech/Music Discrimination For Analysis Of Radio Stations - 2017

ABSTRACT:

A computationally economical feature, referred to as Minimum Energy Density (MED) was applied to discriminate audio signals between speech and music in the radio stations programs. The presented binary classifier is based on testing 2 options: energy distribution and differences between energy in channels. We analyzed 240 hours of signals, from ten Polish radio stations. Our analysis permits us to supply info concerning content of particular radio stations.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : Attention in Reasoning Dataset, Analysis, and Modeling ABSTRACT: Although attention has become an increasingly popular component in deep neural networks for the purpose of both interpreting data and improving
PROJECT TITLE :Cost-Optimal Caching for D2D Networks With User Mobility: Modeling, Analysis, and Computational Approaches - 2018ABSTRACT:Caching well-liked files at the user equipments (UEs) provides an efficient way to alleviate
PROJECT TITLE :Design, Analysis, and Implementation of ARPKI: An Attack-Resilient Public-Key Infrastructure - 2018ABSTRACT:This Transport Layer Security (TLS) Public-Key Infrastructure (PKI) is based on a weakest-link security
PROJECT TITLE :Modeling, Analysis, and Scheduling of Cluster Tools With Two Independent ArmsABSTRACT:Twin-armed cluster tools for semiconductor manufacturing sometimes have had two arms fixed in opposite directions. Recently,
PROJECT TITLE :Modeling, Analysis, and Detection of Internal Winding Faults in Power TransformersABSTRACT:The winding interturn fault is critical in power transformers since its result is not simply comprehensible at lower magnitude