1 Department of Electrical and Electronic Engineering, University of Rajshahi, Rajshahi-6205, Bangladesh.
2 Department of Electrical, Electronic and Communication Engineering, Pabna University of Science and Technology, Pabna-6600, Bangladesh.
Research Article
World Journal of Advanced Research and Reviews, 2024, 22(02), 1495-1503
Article DOI: 10.30574/wjarr.2024.22.2.1569
Received on 11 April 2024; revised on 18 May 2024; accepted on 21 May 2024
In many different areas, such as neurophysics, geophysics, and communication, it is vital to effectively handle signals when there is unwanted disturbance. Linear prediction (LP) methods provide precise modeling capabilities for various parametric models and are used in a wide range of fields such as predicting future data, compressing speech, analyzing spectra, filling in missing signals, and decreasing noise. LP is especially beneficial in speech processing systems. Speech analysis and synthesis greatly relies on spectral envelopes, which are closely connected to models of speech production and perception. However, the performance of the LP method may decline when limited information is involved in pitch synchronous analysis. In order to overcome this constraint, we developed the implementation of the Average Weighted Linear Prediction (AWLP) technique, which does not require the use of a window. The AWLP utilizes a signal of weighted prediction error acquired from the autocorrelation process of LP. By performing this action, it provides a more precise estimation of the power spectrum and coefficients used for vocal tract parametric models. Importantly, the effectiveness of the AWLP can be seen in both pitch synchronous and asynchronous analyses, which means it is appropriate for situations where segments are chosen randomly. We confirm the effectiveness of the AWLP technique by employing it on both synthetic voice and real speech. Additionally, we assess its effectiveness by comparing it to the direct autocorrelation technique and a modified autocorrelation (MA) approach. To sum up, the AWLP method presents a hopeful solution for reliable spectral analysis that addresses the divide between pitch synchronous and asynchronous situations.
LP; Autocorrelation; Pitch Synchronous; Pitch Asynchronous; PEF; WPEF
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Md Arifour Rahman, Md Masudur Rahman, Arifuzzaman Joy and Md. Najmul Hossain. Spectrum estimation for voiced speech using average weighted linear prediction. World Journal of Advanced Research and Reviews, 2024, 22(2), 1495-1503. Article DOI: https://doi.org/10.30574/wjarr.2024.22.2.1569