Q2. What is the weight function for the peaks?
A weight function at the ®ne level can be derived from the residual signal energy plot to deemphasize the segments corresponding to the valleys relative to the segments corresponding to the peaks.
Q3. What is the use of the modi®ed residual signal?
The modi®ed residual signal is used to excite the time± varying all-pole ®lter, updated every 2 ms, to generate the enhanced speech.
Q4. What is the weight function for the noise signal?
A weight function is derived from the smoothed inverse ¯atness characteristics in such a way that the residual signal samples in the regions corresponding to low values of the inverse ¯atness are reduced relative to the residual signal samples in the regions corresponding to high values of the inverse ¯atness.
Q5. What is the effect of the spectral contours of speech?
Temporal sequence of these peaks also produces discontinuities in the contours of the spectral peaks when compared with the smooth contours encountered in natural speech.
Q6. What is the effect of the thresholds on the speech quality?
The setting of various thresholds in the processing is primarily dictated by the listener's tolerance to annoyance due to noise and preference to speech quality.
Q7. What is the LP residual signal of noisy speech?
The LP residual signal of noisy speech was modi®ed retaining only the 2 ms portions of the residual signal around the instants of excitation.
Q8. What is the effect of the parameter on the quality of speech?
The choice of the parameters depends on listener's preference, as the e ect of these parameters on the resulting quality of the enhanced speech is gradual and not abrupt.
Q9. What is the weight function for the inverse spectral atness plot?
A mapping function of the type shown in Fig. 2 can be used to map the smoothed inverse spectral ¯atness values to the weight values for each short (2 ms) frame of residual signal.
Q10. What is the weighting of the residual signal at the ne level?
Note that the weighting of the residual signal at the ®ne level (i.e. relative emphasis of the residual signal samples within a glottal cycle) should be mild to avoid distortion in the processed speech.
Q11. How is the inverse spectral atness plot derived?
The spectral ¯atness characteristics are derived by comparing the energy in the residual signal with the energy in the noisy speech signal in each short interval of about 2 ms.
Q12. What are the features of the speech enhancement method?
But these features are not useful for enhancement, since for generating the enhanced speech signal one needs both the spectral envelope and excitation for each (short-time) analysis frame.
Q13. Why is the residual signal more like noise than like a signal?
The primary reason for this is that, in the source signal such as the linear prediction (LP) residual signal the samples are uncorrelated and hence the residual samples are more like noise than like a signal.
Q14. What is the energy ratio of the noisy speech signal and the corresponding portion of the residual signal?
For each small window of the residual signal, the energy ratio of the noisy speech signal and the corresponding portion of the residual signal gives anindication of the amount of reduction in the correlation of the signal samples.