Implementation of Pre-Emphasis Analog Filter on Raspberry Pi Using Zero-Order Hold Discretization as a Pre-Processing to Humanoids’ Commands Recognition

https://doi.org/10.22146/juliet.v3i2.71226

Jans Hendry(1*), Budi Sumanto(2), Yoga Mileniandi(3), Putri Mawaring Wening(4)

(1) Department of Electrical Engineering and Informatics, Universitas Gadjah Mada
(2) Department of Electrical Engineering and Informatics, Universitas Gadjah Mada
(3) Department of Electrical Engineering and Informatics, Universitas Gadjah Mada
(4) Department of Electrical Engineering and Informatics, Universitas Gadjah Mada
(*) Corresponding Author

Abstract


Intisari – Dalam teknologi yang menggunakan pengolahan sinyal wicara, tapis pre-emphasis sering digunakan sebelum proses ekstraksi ciri. Tapis ini dapat memperbesar amplitudo dari sinyal pada frekuensi tinggi sambil tetap mempertahankan bagian sinyal pada frekuensi rendah. Dalam penelitian ini, kami menerapkan tapis pre-emphasis analog yang dikembangkan dari tapi pelolos frekuensi tinggi. Lalu, filter tersebut didiskretkan menggunakan metode zero-order hold (ZOH). Kedua filter tersebut memiliki pole yang menunjukkan kestabilan. Nilai pole dari tapis diskret selalu di titik nol, sedangkan nilai zero -0.9375. Hasil rekonstruksi dengan menggunakan tapis ­de-emphasis menunjukkan nilai mean-squared error nol yang menyimpulkan bahwa strategi menggunakan metode frame-by-frame untuk implementasi tapis pre-emphasis sangat dianjurkan.

Kata kunci – pre-emphasis, de-emphasis, mean-squared error, tapis, wicara

Abstract – In speech processing technology, the pre-emphasis filter is often used before feature extraction. This filter can emphasize amplitude with high frequencies while preserving the low frequencies side. In this research, we implemented a complete analog pre-emphasis filter from a conventional analog high-pass filter. Then the analog pre-emphasis filter is discretized using zero-order hold (ZOH). The analog and discrete forms have been shown stable according to pole location. The pole of the discrete form is always at the origin, while zero is -0.9375. The reconstruction result, with the help of the de-emphasis filter, shows no discrepancies over the original, hence the mean-squared error is zero which establishes the conclusion that the frame-by-frame method applies to the pre-emphasis filter is lossless and preferable.

Keywords – pre-emphasis, de-emphasis, mean-squared error, filter, speech

Full Text:

PDF


References

[1] D. Anggraeni, W. S. M. Sanjaya, M. Y. S. Nurasyidiek, and M. Munawwaroh, “The implementation of speech recognition using mel-frequency cepstrum coefficients (MFCC) and support vector machine (SVM) method based on python to control robot arm,” in IOP Conference Series: Materials Science and Engineering, 2018, vol. 288, no. 1, p. 012042.

[2] A. S. Haq, M. Nasrun, C. Setianingsih, and M. A. Murti, “Speech recognition implementation using MFCC and DTW algorithm for home automation,” in Proceeding of the Electrical Engineering Computer Science and Informatics, 2020, vol. 7, no. 2, pp. 78–85.

[3] S. Attawibulkul, B. Kaewkamnerdpong, and Y. Miyanaga, “Noisy speech training in MFCC-based speech recognition with noise suppression toward robot assisted autism therapy,” in 2017 10th Biomedical Engineering International Conference (BMEiCON), 2017, pp. 1–5.

[4] N. Adnene, B. Sabri, and B. Mohammed, “Design and implementation of an automatic speech recognition based voice control system,” 2021.

[5] B. Birch, C. A. Griffiths, and A. Morgan, “Environmental effects on reliability and accuracy of MFCC based voice recognition for industrial human-robot-interaction,” Proc Inst Mech Eng B J Eng Manuf, vol. 235, no. 12, pp. 1939–1948, 2021.

[6] A. F. Isnawati and J. Hendry, “Implementasi Filter Pre-Emphasis untuk Transmisi Sinyal Audio pada Sistem Komunikasi FBMC-OQAM,” Jurnal Nasional Teknik Elektro Dan Teknologi Informasi (JNTETI), vol. 8, no. 4, pp. 340–346, 2019.

[7] I. McLoughlin, Applied speech and audio processing: with Matlab examples. Cambridge University Press, 2009.



DOI: https://doi.org/10.22146/juliet.v3i2.71226

Article Metrics

Abstract views : 1201 | views : 1392

Refbacks



SINTA 4 accredited based on Decree of the Minister of Research, Technology and Higher Education, Republic of Indonesia Number 225/E/KPT/2022, Vol. 2 No. 1 (2020) - Vol. 6 No. 1 (2025)

e-ISSN: 2746-2536