DocumentCode :
233372
Title :
Sound masking using Genetic Algorithm & Artificial Neural Network (SMUGAANN)
Author :
Culibrina, Francisco B. ; Dadios, Elmer P.
Author_Institution :
Gokongwei Coll. of Eng., De La Salle Univ., Manila, Philippines
fYear :
2014
fDate :
12-16 Nov. 2014
Firstpage :
1
Lastpage :
6
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.
Keywords :
genetic algorithms; hearing; neural nets; speech intelligibility; SMUGAANN; SSA technique; audible sound; evolutionary method; sound masking using genetic algorithm and artificial neural network; sound synthesis algorithm technique; target sound analysis; Artificial neural networks; Conferences; Genetic algorithms; Information technology; Nanotechnology; Noise; The Institute; Artificial Neural Network; Genetic Algorithm; SMUGAAN; SSA; Sound Masking; Sound Pressure Level; Sound Source Separation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM), 2014 International Conference on
Conference_Location :
Palawan
Print_ISBN :
978-1-4799-4021-9
Type :
conf
DOI :
10.1109/HNICEM.2014.7016190
Filename :
7016190
Link To Document :
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