Using matlab for Speech Signal Analysis

1. Matlab:Speech Signal Analysis

2. Speech Signal Analysis Speech signal processing refers to the manipulation, acquisition, storage, transfer and output of vocal output by a computing machine.

3. Fundamental Frequency estimation – frequency domain The following a sample code for fundamental frequency estimation:

4. Fundamental Frequency estimation - frequency domain

5. Fundamental Frequency estimation - frequency domain To search for the index of the peak in the cepstrum between 1 and 20ms, and then convert back to hertz, use: [c,fx]=max(abs(C(ms1:ms20))); fprintf('Fx=%gHz',fs/(ms1+fx-1));

6. Fundamental Frequency estimation - time domain This code plots the autocorrelation function for a section of speech signal:

8. ms20=fs/50 % minimum speech Fx at 50Hz

9. r=r(ms20+1:2*ms20+1)

10. [rmax,tx]=max(r(ms2:ms20))

12. Foramant Frequency Estimation Formant frequency estimation is demonstrated by using LPC to find the best IIR filter from a section of speech signal and then plotting the filter's frequency response.

13. Foramant Frequency Estimation Formant frequency estimation is demonstrated by using LPC to find the best IIR filter from a section of speech signal and then plotting the filter's frequency response.

14. Foramant Frequency Estimation r=roots(a); r=r(imag(r)>0.01); ffreq=sort(atan2(imag(r),real(r))*fs/(2*pi)); for i=1:length(ffreq) fprintf('Formant %d Frequency %.1f',i,ffreq(i)); end

15. Speech Signal Analysis References: http://www.phon.ucl.ac.uk/courses/spsci/matlab

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