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Research Article |

Error Signal Based Method for Real Time Pitch Extraction from Noisy Speech

Author(s): Mohammad Forhad Hossain1, Nargis Parvi 2, Md. Saifur Rahman3, Pintu Chandra Paul4, and Moinur Rahman5*

Published In : International Journal of Electrical and Electronics Research (IJEER)        Volume 14, Issue 3

Publisher : FOREX Publication

Published : 30 September 2026

e-ISSN : 2347-470X

Page(s) : 842-851

DOI: https://doi.org/10.37391/IJEER.140318

Abstract

Pitch estimation efficiency always gets affected by two major phenomena. The first one is additive noise which by nature are not correlated with the source speech signal. The second one is the vocal tract effect which creates unnecessary peaks within the signal waveform, resulting inaccurate detection of the pitch value. This paper proposes a Modified Weighted Autocorrelation Function (MWAF) executed in the Linear Predictive Coding (LPC) residual domain, instead of directly executing over the noisy source speech signal. Converting the noisy source speech signal to LP residual helps eliminating the vocal tract effects and emphasizing the necessary effects of glottal excitation. The Autocorrelation Function (ACF) and the Circular Average Magnitude Difference Function (CAMDF) are directly applied on this residual. The proposed MWAF is then calculated by multiplying the ACF with the reciprocal of the CAMDF, which enhances the periodic components as well as reduces the noise induced false peaks. Experimental results were evaluated on the KEELE and NTT databases across White, Babble, Train and HF Channel noise conditions. The result shows that our proposed algorithm reduces the Gross Pitch Error (GPE) by an average of 40.34% compared to baseline methods such as BaNa, PEFAC and WAF. Furthermore, the algorithm achieves an overall computational gain of 53.44% compared to BaNa, PEFAC and WAF, offering a stable solution for pitch tracking in degraded acoustic conditions.

Keywords: Pitch, Linear Predictive Coding, Modified Weighted Autocorrelation, LPC Residual.




Mohammad Forhad Hossain , Department of ICT, Comilla University, Bangladesh; Email: forhad-ict-cou@stud.cou.ac.bd

Nargis Parvin , Associate Professor, Department of CSE, Bangladesh Army International University of Science and Technology, Bangladesh; Email: nargis.cse@baiust.ac.bd

Md. Saifur Rahman, Professor, Department of ICT, Comilla University, Bangladesh; Email: saifurice@cou.ac.bd

Pintu Chandra Paul, Assistant Professor, Department of ICT, Comilla University, Bangladesh; Email: pintu@cou.ac.bd

Moinur Rahman , Lecturer, Department of ICT, Comilla University, Bangladesh; Email: moinur.rahman@cou.ac.bd

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Mohammad Forhad Hossain, Nargis Parvin, Md. Saifur Rahman, Pintu Chandra Paul, and Moinur Rahman (2026), Error Signal Based Method for Real Time Pitch Extraction from Noisy Speech . IJEER 14(3), 842-851. DOI: 10.37391/IJEER.140318.