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• W170503053 abstract "Window theory always an active topic of research in digital signal processing. It is mainly used for leakage reduction in spectral analysis. In this paper, the effect of windowing in power spectral density estimation of Tamil speech signal is analyzed. Four different window functions are implemented and their performances are evaluated based on the parameters such as sidelobe level, fall off and gain. Based on the experiments it is found that the effect of applying hamming window best suites for the Tamil speech signal. It can reduce the spectral discontinuities of the signal and this effect of hamming window is given as the potent metric for estimating the spectral power of Tamil speech signal. Here Power Spectral Density (PSD) estimation is computed by using parametric and non-parametric methods. The reduction of noise ratio in PSD is considered as the parameter and it is estimated through crest factor. Finally the paper concludes with the need of best windowing method for PSD particularly in parametric techniques. Evaluation is handled both objectively and subjectively for Tamil speech datasets." @default.
• W170503053 created "2016-06-24" @default.
• W170503053 creator A5002667732 @default.
• W170503053 creator A5041492668 @default.
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• W170503053 date "2011-01-01" @default.
• W170503053 modified "2023-09-25" @default.
• W170503053 title "Power Spectral Density Estimation Using Yule Walker AR Method for Tamil Speech Signal" @default.
• W170503053 cites W1586001298 @default.
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• W170503053 doi "https://doi.org/10.1007/978-3-642-19403-0_49" @default.
• W170503053 hasPublicationYear "2011" @default.
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