Sound masking using genetic algorithm & artificial neural network (SMUGAANN)

College

Gokongwei College of Engineering

Department/Unit

Manufacturing Engineering and Management

Document Type

Conference Proceeding

Source Title

2014 International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management, HNICEM 2014 - 7th HNICEM 2014 Joint with 6th International Symposium on Computational Intelligence and Intelligent Informatics, co-located with 10th ERDT Conference

Publication Date

1-1-2014

Abstract

One of the significant factor of privacy is the source of sound. It creates the level that determines the effectiveness of the other factor. To experience maximum privacy, cancelling of unwanted sound is necessary. To automate the design of sound masking, this proposal use Genetic Algorithm and Artificial Neural Network (SMUGAAN). By evolutionary method two stages are use: a) to determine the target sound being mask evaluation of the parameters of functional elements and b) analysis of the target sound to get the fitness value to be mask and test signals with the help of Sound Synthesis Algorithm (SSA) technique. This stage gives audible sound to mask the target sound. © 2014 IEEE.

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Digitial Object Identifier (DOI)

10.1109/HNICEM.2014.7016190

Disciplines

Manufacturing

Keywords

Soundproofing; Computational auditory scene analysis; Genetic algorithms; Sound pressure; Neural networks (Computer science)

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