Simulation of Noise Removal in Sound Signals by Using Fast Fourier Transform Method

Authors

  • Redza Dwi Septiawan Universitas Mataram
  • Putri Rahmasari Rayes Universitas Mataram
  • Nuzla Af'idatur Robbaniyyah Universitas Mataram

DOI:

https://doi.org/10.29303/semeton.v1i1.203

Keywords:

Simulation, Sounds signal, Noise, Fast Fourier Transform

Abstract

Sound signals are widely used such as when communicating, recording, or medical testing. However, voice signals are often contaminated by noise or interference which can reduce the quality and clarity of sound caused by weather, being in crowded places and other factors. Therefore, noise reduction in voice signals is important in voice signal processing. This study aims to reduce noise in voice signals using the FFT method. The Fast Fourier Transform (FFT) method is used to identify frequencies and reduce noise in voice signals. The data used is in the form of recordings, namely the sound of speech and the sound of rain as noise. This research was conducted with the help of MATLAB R2022a software. The results of this study indicate that the FFT method is effective in reducing noise in the voice signal and improving the sound quality to be cleaner and clearer than the original sound signal before noise removal is performed.

References

Haizar, M. R., Rizki, M., Robbaniyyah, N. A. I., Syechah, B. N., Salwa, S., & Awalushaumi, L. (2024). Numerical Solution of the Korteweg-De Vries Equation Using Finite Difference Method.EIGEN MATHEMATICS JOURNAL,7(1), 97-103.

Putra, Yeffry Handoko. (2006). Teori Sistem dan dasar Sinyal. Talitha Khoum.

Pah, Nemuel Daniel. (2018).Pemrosesan Sinyal Digital.Graha Ilmu.

Irtawaty, A. S., Ulfah, M., & Rukhyah, S. F. (2019). Implementasi Metode Fast Fourier Transform (FFT) Dalam Mengklasifikasikan Suara Pria dan Wanita di Laboratorium Jurusan.Jurnal Terpadu Teknologi,7(2).

Kusuma, D. T. (2020). Fast Fourier Transform (FFT) Dalam Transformasi Sinyal Frekuensi Suara Sebagai Upaya Perolehan Average Energy (AE) Musik.

Sugianta, K. A. (2020). Analisis Pola Bunyi Sunari Berdasarkan Metode Fast Fourier Transform.Jurnal Ilmu Komputer Indonesia,5(2), 14-21.

Robbaniyyah, N. A. I. (2022). Pengembangan Metode Iterasi Petviashvili dalam Penentuan Solusi Gelombang Stasioner pada Persamaan Bertipe Schrödinger Nonlinear dengan Fungsi Potensial V (x).EIGEN MATHEMATICS JOURNAL, 47-53.

Deng, L., & Li, X. (2013). Machine learning paradigms for speech recognition: An overview.IEEE Transactions on Audio, Speech, and Language Processing,21(5), 1060-1089.

Bimantara, A. A., Adhi, M. S., Priambodo, D., Azhar, H. M., & Junaidi, A. (2019). Simulasi Penghilangan Noise Pada Sinyal Suara Menggunakan Metode Fast Fourier Transform (FFT).Journal of Informatics Information System Software Engineering and Applications (INISTA),1(2), 20-25.

Cahyono, B. (2016). Penggunaan Software Matrix Laboratory (Matlab) Dalam Pembelajaran AljabarLinier. Phenomenon: Jurnal Pendidikan MIPA, 3 (1), 45–62.

Published

2024-04-30

How to Cite

Septiawan, R. D., Rayes, P. R., & Robbaniyyah, N. A. (2024). Simulation of Noise Removal in Sound Signals by Using Fast Fourier Transform Method. Semeton Mathematics Journal, 1(1), 1–7. https://doi.org/10.29303/semeton.v1i1.203

Issue

Section

Articles