HUMAN VOICE SEPARATION BASED ON GENDER USING THE FAST FOURIER TRANSFORM (FFT)

  • Lela Sari Kristina Institut Teknologi Telkom Purwokerto
  • Gita Fadila Fitriana Institut Teknologi Telkom Purwokerto
  • Agi Prasetiadi Institut Teknologi Telkom Purwokerto

Abstract

 Voice is one of the characteristics possessed by humans. One of the human abilities to identify someone by seeing and hearing. Through this ability one can easily distinguish gender, based on physical and voice categories. voices that previously can be recognized easily by humans, for now can also be recognized by computers, which aims to separate sounds based on gender. The final result of this research is to know the average error of data objects that have been inputted with the algorithm used in this study is the Fast Fourier Transform. The results of the implementation process of the Fast Fourier Transform Algorithm show whether or not the average sound error is influenced by the high or low amplitude of the sound being tested and from the results obtained the average error amplitude of the female voice is lower than the average error amplitude. Male voice. Of the two sources of human voices used, the lowest average error was produced in the 7th cluster for Female 3 votes with an average error result of 132.840, while the results of trials conducted with 3 sound sources resulted in the lowest average error in the second cluster. -3 for Female 3 votes with an average error result of 212,976, and for the four sound sources used it produces the lowest average error in the 3rd cluster on Mela's voice with an average error result of 217,462.

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Published
2020-12-18