Matlab: Speech Signal Analysis

  • 3,733 views
Uploaded on

Using matlab for Speech Signal Analysis

Using matlab for Speech Signal Analysis

More in: Technology
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
No Downloads

Views

Total Views
3,733
On Slideshare
0
From Embeds
0
Number of Embeds
0

Actions

Shares
Downloads
0
Comments
0
Likes
2

Embeds 0

No embeds

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
    No notes for slide

Transcript

  • 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:
  • 7. Fundamental Frequency estimation - time domain
    • ms2=fs/500                 % maximum speech Fx at 500Hz
    • 8. ms20=fs/50                 % minimum speech Fx at 50Hz
    • 9. r=r(ms20+1:2*ms20+1)
    • 10. [rmax,tx]=max(r(ms2:ms20))
    • 11. fprintf('rmax=%g Fx=%gHz ',rmax,fs/(ms2+tx-1));
  • Fundamental Frequency estimation - time domain
  • 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
  • 16. Visit more self help tutorials
    Pick a tutorial of your choice and browse through it at your own pace.
    The tutorials section is free, self-guiding and will not involve any additional support.
    Visit us at www.dataminingtools.net