Murthy M.B.Rama

Publications (2)0 Total impact

• Source

  Available from: ijcaonline.org

  Article: Speech Enhancement using a Modified Apriori SNR and Adaptive Spectral Gain Control

  Rao Ch.V.Rama, Murthy M.B.Rama, Rao K.Srinivasa
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  ABSTRACT: A new approach to single channel speech enhancement is proposed using a modified a priori SNR and spectral gain control. The proposed approach is first directed toward finding self adaptive averaging factor to estimate the apriori SNR. Next, spectral gain is reduced in order to suppress effects of the noise in the speech absent frames. Further, in the speech present frames, in order to reduce signal distortion, the spectral gain is controlled to be unity based on an SNR calculated by using a ridgeline spectrum. Finally, the original noisy speech is added to the estimated speech in a ratio is controlled by the long term averaged SNR of the estimated noise and the noisy speech. Computer simulations by using speech signals, the white noise, the car noise and the babble noise have been carried out using several available methods and the proposed method. It is observed that there is improvement in speech quality by the proposed method.
  International Journal of Computer Applications. 01/2011;
• Source

  Available from: airccse.org

  Article: Noise Reduction Using mel-Scale Spectral Subtraction with Perceptually Defined Subtraction Parameters- A New Scheme

  Rao Ch.V.Rama, Murthy M.B.Rama, Rao K.Srinivasa
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  ABSTRACT: The noise signal does not affect uniformly the speech signal over the whole spectrum isn the case ofcolored noise. In order to deal with speech improvement in such situations a new spectral subtractionalgorithm is proposed for reducing colored noise from noise corrupted speech. The spectrum is dividedinto frequency sub-bands based on a nonlinear multiband bark scale. For each sub-band, the noisecorrupted speech power in past and present time frames is compared to statistics of the noise power toimprove the determination of the presence or absence of speech. During the subtraction process, a largerproportion of noise is removed from sub-bands that do not contain speech. For sub-bands that containspeech, a function is developed which allows for the removal of less noise during relatively low amplitudespeech and more noise during relatively high amplitude speech .Further the performance of the spectralsubtraction is improved by formulating process without neglecting the cross correlation between the speechsignal and background noise. Residual noise can be masked by exploiting the masking properties of thehuman auditory system. In the proposed method subtraction parameters are adaptively adjusted usingnoise masking threshold. A psychoacoustically motivated weighting filter was included to eliminateresidual musical noise. Experimental results show that the algorithm removes more colored noise withoutremoving the relatively low amplitude speech at the beginning and ending of words.
  Signal & Image Processing. 01/2011;