1 / 9

Spectral Analysis & Spectrogram

Spectral Analysis & Spectrogram. SASPL Cheolwoo Jo. Contents. Spectral Analysis Spectrogram Narrow Band Wide Band Analysis of Spectrogram AR, MA, ARMA model of Speech. Spectral Analysis. Spectrogram in matlab. [B,F,T] = SPECGRAM(A,NFFT,Fs,WINDOW,NOVERLAP) A: Speech Signal

beau
Télécharger la présentation

Spectral Analysis & Spectrogram

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Spectral Analysis & Spectrogram SASPL Cheolwoo Jo

  2. Contents • Spectral Analysis • Spectrogram Narrow Band Wide Band • Analysis of Spectrogram • AR, MA, ARMA model of Speech

  3. Spectral Analysis

  4. Spectrogram in matlab • [B,F,T] = SPECGRAM(A,NFFT,Fs,WINDOW,NOVERLAP) • A: Speech Signal • NFFT: Number of samples • Fs: Sampling Frequency • Window: Type of Window • NOVERLAP: Number of Overlapping signal

  5. function [array,raw] = spectrogram(wave,segsize,nlap,ntrans); %function array = spectrogram(wave,segsize,nlap,ntrans); % defaults spectrogram(wave,128,8,4) % nlap is number of hamming windows overlapping a point; % ntrans is factor by which transform is bigger than segment; % returns a spectrogram 'array' with fourth root of power, % filter smoothed and formatted for display. % Added option to return raw spectrogram.... Malcolm 5/26/95 % Added code so that input could be any direction ... Malcolm 5/26/95 % (c) 1998 Interval Research Corporation if nargin < 4; ntrans=4; end if nargin < 3; nlap=8; end if nargin < 2; segsize=128; end [r c] = size(wave); if (r < c) wave = filter([1 -0.95],[1],wave'); else wave = filter([1 -0.95],[1],wave); end Spectrogram in auditory toolbox

  6. s = length(wave); nsegs = floor(s/(segsize/nlap))-nlap+1; array = zeros(ntrans/2*segsize,nsegs); window = 0.54-0.46*cos(2*pi/(segsize+1)*(1:segsize)'); for i = 1:nsegs seg = zeros(ntrans*segsize,1); % leave half full of zeroes seg(1:segsize) = ... window.*wave(((i-1)*segsize/nlap+1):((i+nlap-1)*segsize/nlap)); seg = abs(fft(seg)); % reverse for image display array(:,i) = seg(((ntrans/2*segsize)+1):(ntrans*segsize)); end if nargout > 1 raw = array; end

  7. array = array .* array; % back into power domain for smoothing for i=1:nsegs % smooth the spectral slices array(:,i) = filter([.2 1 .2],[1],array(:,i)); end for i=1:ntrans/2*segsize % smooth the channels array(i,:) = filter([.2 1 .2],[1],array(i,:)); end % compress with square root of amplitude (fourth root of power) off = 0.0001*max(max(array)); % low end stabilization offset, array = (off+array).^0.25-off^0.25; % better than a threshold hack! array = 255/max(max(array))*array;

  8. Spectrogram level scaling • Log|x[k]|2 Gray Intensity Black Log Energy(dB) White 60dB

  9. Specgram • SPECGRAM(A,F,Fs,WINDOW) • Matlab • A: Speech • F: Vector of Frequencies • Fs: Sampling Frequency • Window: Type of Window Function

More Related