SOUND CONVERTION USING FAST FOURIER TRANSFORM ALGORITHM

Hendrawan, Tan Ferrdy (2016) SOUND CONVERTION USING FAST FOURIER TRANSFORM ALGORITHM. Other thesis, Fakultas Ilmu Komputer UNIKA Soegijapranata.

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Abstract

Voice Converter is a program where the user can change the octave of the input file to higher octave or lower octave. The file type that can be processed is wav file only. The wav file that will be used is 8bit wav file. This project is created with Java language programming and use one dimension array, linked list and array list as data structure. The one dimension array will be used to store the processed analog signal data from wav file and for processing the voice convention of voice. The linked list and array list will be used to process the K-means Algorithm for clustering the signal data to determine what gender it is. For convert the input file from user , the project will using FFT(Fast Fourier Transform) algorithm. Fast Fourier Transform is method to converts a signals from its original domain to a representation in the frequency domain. After doing various experiments with the program, the results show that the voice color characteristic that makes the different between female and male gender still cannot achieved. The only achieved experiments results just know the different concept of wav file data reading sample that if the sample rate (how much data sample readed each second) is 22050 with 20000 data sample is the same as 44100 sample rate with 40000 data sample, the FFT Algorithm that being used in this final project is still not the best method to change the voice because still cannot change the timbre(voice color that distinguishes between male and female) and has a lot of noise after processing, but the convention the voice octave to higher or lower octave can be achieved. The noise of processed data of FFT Algorithm can be reduced using Low Pass Filtering Algorithm.

Item Type:	Thesis (Other)
Subjects:	000 Computer Science, Information and General Works > 005 Computer programming, programs & data
Divisions:	Faculty of Computer Science > Department of Informatics Engineering
Depositing User:	Mr Ign. Setya Dwiana
Date Deposited:	31 May 2016 06:24
Last Modified:	29 Aug 2022 07:52
URI:	http://repository.unika.ac.id/id/eprint/9713

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