• 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