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• W2508650282 abstract "Presence of noise increases the dimension of the information. A noise suppression algorithm is developed with an idea of combining the General Kalman Filter and Estimate Maximization (EM) frame work.This combination is helpful and effective in identifying noise characteristics of an acoustic environment. Recursion between Estimate step and Maximization step enabled the algorithm to deal any model of noise. The same Speech enhancement procedure in applied in the pre-processing stage of a conventional Speaker identification method. Due to the non-stationary nature of noise and speech adaptive algorithms are required. Algorithm is first applied for Speech enhancement problem and then extended to using it in the pre-processing step of the Speaker identification. The present work is compared in terms of significant metrics with existing and popular algorithms and results show that the developed algorithm is dominant over them." @default.
• W2508650282 created "2016-09-16" @default.
• W2508650282 creator A5039395849 @default.
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• W2508650282 date "2016-08-30" @default.
• W2508650282 modified "2023-09-24" @default.
• W2508650282 title "General Kalman Filter & Speech Enhancement for Speaker Identification" @default.
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• W2508650282 doi "https://doi.org/10.5121/ijci.2016.5414" @default.
• W2508650282 hasPublicationYear "2016" @default.
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