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Noise Estimation Using Standard Deviation of the Frequency Magnitude Spectrum for Mixed Non-Stationary Noise


Affiliations
1 Department of Master of Computer Applications, Dr. SNS Rajalakshmi College of Arts and Science, India
2 Department of Computer Science, Bharathiar University, India
     

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Noise estimation and suppression is very important for improving the quality of speech signal. Noises exist in almost all places. In reality, more than one noise degrades the speech signal. It is hard to find and supress various types of noise that affect the speech quality. This paper proposed a method for noise estimation of mixed non-stationary noisy speech signal. This method uses Spectral properties of the noisy speech signal to detect the frequency regions of noise signal. Highest frequency of speech signal is calculated and it is considered as the threshold value for separating noise signal and clean speech signal. Using Spectral subtraction, Standard deviation of noise spectrum is subtracted with noisy spectrum to acquire enhanced speech signal. Performance of the method is evaluated using SNR and Spectrogram. The main focus of this paper is to propose an independent method which estimates the noise of any type and nature.

Keywords

Noise Estimation, Spectral Subtraction, Standard Deviation, SNR, Spectrogram.
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  • Noise Estimation Using Standard Deviation of the Frequency Magnitude Spectrum for Mixed Non-Stationary Noise

Abstract Views: 261  |  PDF Views: 2

Authors

A. Indumathi
Department of Master of Computer Applications, Dr. SNS Rajalakshmi College of Arts and Science, India
E. Chandra
Department of Computer Science, Bharathiar University, India

Abstract


Noise estimation and suppression is very important for improving the quality of speech signal. Noises exist in almost all places. In reality, more than one noise degrades the speech signal. It is hard to find and supress various types of noise that affect the speech quality. This paper proposed a method for noise estimation of mixed non-stationary noisy speech signal. This method uses Spectral properties of the noisy speech signal to detect the frequency regions of noise signal. Highest frequency of speech signal is calculated and it is considered as the threshold value for separating noise signal and clean speech signal. Using Spectral subtraction, Standard deviation of noise spectrum is subtracted with noisy spectrum to acquire enhanced speech signal. Performance of the method is evaluated using SNR and Spectrogram. The main focus of this paper is to propose an independent method which estimates the noise of any type and nature.

Keywords


Noise Estimation, Spectral Subtraction, Standard Deviation, SNR, Spectrogram.

References