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- W187652810 abstract "Manifestation of noise-in-speech is inherent unless a conscious effort is made to minimize the disturbances in the surroundings while recording speech. The performance of a speech recognition system often degrades in the presence of noise. In this paper, we study the effect of noise in the speech signal on the extracted speech features that are used in speech recognition. Mel frequency cepstral coefficients (MFCCs) are the most popularly used speech features in speech and speaker recognition applications. We first show theoretically, how additive Gaussian noise with mean, µ and variance, σ2 effects the speech parameters (MFCCs). The mean and variance of the error in MFCC due to noise-in-speech is related to the mean and variance of the noise added. We experimentally verify that additive Gaussian noise-in-speech results in an error in MFCC parameter estimation which is also Gaussian." @default.
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- W187652810 date "2009-09-03" @default.
- W187652810 modified "2023-09-27" @default.
- W187652810 title "Effect of noise-in-speech on MFCC parameters" @default.
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