Advances and Applications in Statistics

The Advances and Applications in Statistics is an internationally recognized journal indexed in the Emerging Sources Citation Index (ESCI). It provides a platform for original research papers and survey articles in all areas of statistics, both computational and experimental in nature.

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AUDIO SIGNALS RECOVERY WITH TIME-FREQUENCY ESTIMATION USING SHORT-TIME FOURIER TRANSFORM

Authors

  • Rhegie M. Caga-anan

Keywords:

short time Fourier transform, time-domain, frequency-domain, time-frequency domain

DOI:

https://doi.org/10.17654/0972361725065

Abstract

Recovered audio signals contain serviceable information. In the context of audio signal analysis, the best trade-off between frequency estimation and time has to be made due to Heisenberg’s principle [2] which asserts that we cannot obtain the specific frequency,  and time, t with the same amount of precision simultaneously. In this study, we use higher moments in attempting to reconstruct the time series data,  and in finding an optimal bin size of the time window using short time Fourier transform. The performance of these two estimators, Doane and modified Doane, has been studied based on their mean squared errors (MSE).

Received: April 10, 2025
Revised: August 3, 2025
Accepted: August 12, 2025

References

[1] J. Fourier, Théorie analytique de la chaleur (The Analytical Theory of Heat), Encyclopedia Britannica, 1822.

[2] W. Heisenberg, Heisenberg Uncertainty Principle or Indeterminancy Principle, Encyclopedia Britannica, 1927.

[3] D. Gabor, Theory of communication, Journal of the Institution of Electrical Engineers 93 (1946), 429-441.

[4] R. Bracewell, The Fourier transform, Scientific American 260 (1989), 86-9, 92-5.

[5] D. W. Scott, Probability Density Estimation, International Encyclopedia of the Social & Behavioral Sciences, 2001.

[6] R. Abdelmalek, Z. Mnasri and F. Benzarti, Audio signal reconstruction using phase retrieval: Implementation and evaluation, Multimedia Tools and Applications 81 (2022), 15919-15946.

[7] A. Elbir, H. O. İlhan, G. Serbes and N. Aydın, Short Time Fourier Transform based music genre classification, 2018 Electric Electronics, Computer Science, Biomedical Engineerings’ Meeting (EBBT), Istanbul, Turkey, 2018, pp. 1-4. DOI: 10.1109/EBBT.2018.8391437.

[8] Q. Liu, X. Wu and X. Ma, An automatic segmentation method for heart sounds, Biomedical Engineering Online 17 (2018), 106, 17 pp. DOI: 10.1186/s12938-018-0538-9. PMCID: PMC6080363; PMID: 30081909.

[9] C. Mateo and J. A. Talavera, Short-Time Fourier Transform with the Window Size Fixed in the Frequency Domain (STFT-FD): Implementation, SoftwareX 8 (2018), 5-8. https://doi.org/10.1016/j.softx.2017.11.005.

[10] Z. A. Cheddad and A. Cheddad, Active restoration of lost audio signals using machine learning and latent information, intelligent systems and applications, IntelliSys 2023, Lecture Notes in Networks and Systems, vol. 822, Springer, Cham, 2024.

Published

23-09-2025

Issue

Section

Articles

How to Cite

AUDIO SIGNALS RECOVERY WITH TIME-FREQUENCY ESTIMATION USING SHORT-TIME FOURIER TRANSFORM. (2025). Advances and Applications in Statistics , 92(10), 1503-1515. https://doi.org/10.17654/0972361725065

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