Unified Approach to Identification and Analysis of Noise in speech processingSystems

K. V. Ratna Prabha1,V Vamsi Sudheera, N. Lavanya

The mathematical representation of any entity is in the ideal conditions without considering the effects real world interferences. Any form of physical quantity which interacts with physical phenomena’s causes an arbitrary change based on their interference level. Considering a speech signal, communication signaling, sensor signals, even the image capturing, and processing have to deal with them. This type of unwanted energy tending to interfere with the signals termed as Noise has become to increase its sources. Today a world dwelled with the various electronic, mechanical, electrical and many devices which are also communicating through various electromagnetic signals increasing the Noise sources significantly. The problem of identifying and removing noise is challenging when they are of widely differing sources and forms. This paper aims to design intelligent algorithms to make full use of the signaling data to identify and classify Noise. As an important discipline, machine learning includes pattern recognition and clustering techniques to identify deterministic and no deterministic noises and help to generate an optimal action to improve the quality of service. The present study aims at providing a tool to identify, mathematicised and analyze all possible noises in any system. This paper discusses the scope of machine learning algorithms to identify and analysis of noise for any give signals and images. We conclude the paper with implementing this approach to simulated speech signals

Volume 11 | 02-Special Issue

Pages: 1439-1445