NOISE REDUCTION IN SPEECH
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03032011, 09:50 AM
PRESENTED BY: K.AKILA N.DEEPTHA D.NARMADA final ppt.ppt (Size: 1.18 MB / Downloads: 63) NOISE REDUCTION IN SPEECH • Noise is an unwanted disturbance superimposed on a useful signal, which tends to obscure its information content. • The background noise is the most common factor degrading the quality and intelligibility of speech . • The noise reduction technique intends to lower the noise level without affecting the quality of speech signal. OBJECTIVE • To achieve intelligibility, naturalness and overall perceptual quality of the speech signal. • To improve the signal strength. NOISE DATA Factory Noise HF Channel Noise Babble Noise White Noise Pink Noise Car Interior Noise Cockpit Noise N.S  Noisy Speech A.C  Approximation Coefficients D.C  Detail Coefficients ICA  Independent Component Analysis ZCR  Zero Crossing Rate N.R.S  Noise Reduced Speech STANDARD DATABASE SPEECH SIGNAL : TEXT : SHE HAD YOUR DARK SUIT IN GREASY WASH WATER ALL YEAR SAMPLE LENGTH : 63488 samples SAMPLING FREQUENCY :16000Hz VARIANCE :E(X2)(E(X))2 Variance of the SPEECH SIGNAL(in dB) : 74.5232 ORIGINAL SPEECH SIGNAL FREQUENCIES IN THE SPEECH SIGNAL FREQUENCIES IN THE NOISE NOISY SPEECH SIGNAL FREQUENCIES IN THE NOISY SPEECH VARIANCE :E(X2)(E(X))2 Variance of the SPEECH SIGNAL(in dB) : 74.5232 Variance of the NOISE(in dB) : 106.1482 Variance of the NOISY SPEECH(in dB) : 74.1012 FRAMING NONOVERLAPPING FRAMES OF 16msec DURATION. NUMBER OF FRAMES :248 WAVELET DECOMPOSITION WAVELET USED  DAUBECHIES WAVELET db1 DECOMPOSITION LEVEL  LEVEL 2 APPROXIMATION COEFFICIENTS : Correspond to speech combined with low frequency noise in the frequency band (02000Hz). DETAIL COEFFICIENTS : Correspond to the contribution due to speech in the frequency band (20004000Hz). WAVELET RECONSTRUCTION APPROXIMATION COEFFICIENTS AND DETAIL COEFFICIENTS are UPSAMPLED. RECONSTRUCTED SIGNAL Variance of the RECONSTRUCTED SIGNAL in(02000 Hz) (in dB) : 76.4146 EXTRACTION OF NOISE FROM NOISY SPEECH To analyze the noise frequencies, we need to extract the noise from noisy speech. Wavelet transform of LEVEL 2 is used to extract the speech in low frequency band (02000 Hz) and to find the starting frame. A Modified probability density function is calculated. A negative wavelet entropy computed using modified probability density function is used for determining the starting frame. MODIFIED PROBABILITY DENSITY FUNCTION iframe number jsample in a frame Wi(j) –wavelet energy of the jth sample in ith frame Kpositive constant=1.8 NEGATIVE ENTROPY CALCULATION The negative wavelet entropy is given as E(i) = Pi(j)*log(Pi(j)) Pi(j) Modified probability function The negative wavelet entropy is more negative for noise and silence frames and less negative for speech frames. Starting frame is determined from the entropy comparison ENTROPY PLOT DETERMINING THE STARTING FRAME A THRESHOLD is set THRESHOLD=(MEAN(entropy)+MEDIAN(entropy))/2 THRESHOLD= 74.32 STARTING FRAME :46 The ending frame is also determined. END FRAME : 234 BOUNDARY PLOT CONCLUSION Variance of the NOISY SPEECH(in dB)= 74.1012 Variance of the RECONSTRUCTED = 76.4146 SIGNAL from wavelet decomposition (in dB) There is an improvement in the intelligibility of the noisy speech which is proved by hearing the speech at each stage. 


