Matlab: Speech Signal Analysis
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This document discusses various methods for analyzing speech signals using Matlab, including fundamental frequency estimation in both the frequency and time domains, and formant frequency estimation using linear predictive coding. Code examples are provided for estimating fundamental frequency from the peak in a signal's cepstrum and autocorrelation function, and for using LPC to find the best IIR filter for a speech segment and plot the filter's frequency response to estimate formant frequencies.
![Fundamental Frequency estimation - frequency domainTo 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\n',fs/(ms1+fx-1));](https://image.slidesharecdn.com/speechsignalanalysis-100108092003-phpapp02/85/Matlab-Speech-Signal-Analysis-5-320.jpg)
![[rmax,tx]=max(r(ms2:ms20))](https://image.slidesharecdn.com/speechsignalanalysis-100108092003-phpapp02/85/Matlab-Speech-Signal-Analysis-10-320.jpg)
Matlab: Speech Signal Analysis
- 2. Speech Signal AnalysisSpeech signal processing refers to the manipulation, acquisition, storage, transfer and output of vocal output by a computing machine.
- 3. Fundamental Frequency estimation – frequency domainThe following a sample code for fundamental frequency estimation:
- 4. Fundamental Frequency estimation - frequency domain
- 5. Fundamental Frequency estimation - frequency domainTo 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\n',fs/(ms1+fx-1));
- 6. Fundamental Frequency estimation - time domainThis code plots the autocorrelation function for a section of speech signal:
- 7. Fundamental Frequency estimation - time domainms2=fs/500 % maximum speech Fx at 500Hz
- 8. ms20=fs/50 % minimum speech Fx at 50Hz
- 11. fprintf('rmax=%g Fx=%gHz\n',rmax,fs/(ms2+tx-1));Fundamental Frequency estimation - time domain
- 12. Foramant Frequency EstimationFormant 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 EstimationFormant 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 Estimationr=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\n',i,ffreq(i));end
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