【语音增强】卡尔曼滤波法语音增强（含滤波前后语谱图对比）【含Matlab源码 4076期】.zip

%______________________________________________________________________________________________________________________ % % @file myspectrogram.m % @date 17/09/2007 % @author Kamil Wojcicki % @affiliation Signal Processing Laboratory, Griffith University, Nathan QLD4111, Australia % @brief Spectrogram function %______________________________________________________________________________________________________________________ % % @inputs speech - time domain speech signal vector % fs - sampling frequency (Hz), f.e. 8000 % T - vector of frame width, Tw, and frame shift, Ts, in milliseconds, i.e. [Tw, Ts] % w - analysis window handle, f.e. @hamming % nfft - fft analysis length, f.e. 1024 % Slim - vector of spectrogram limits (dB), i.e. [Smin Smax] % alpha - fir pre-emphasis filter coefficients, f.e. [1 -0.97] % cmap - color map ('default', 'gray', 'bone', 'copper', 'hot', 'jet') % cbar - color bar (boolean) % type - estimator or feature type ('lp', 'per') % % @output handle - plot handle %______________________________________________________________________________________________________________________ % % @usage [handle] = myspectrogram(speech, fs, T, w, nfft, Slim, alpha, cmap, cbar, type); % % @examples [handle] = myspectrogram(speech, 8000, [18 1], @hamming, 1024, [-45 -2], false, 'default', false, 'lp'); % [handle] = myspectrogram(speech, 8000, [18 1], @hamming, 1024, [-45 -2], [1 -0.97], 'default', true, 'per'); %______________________________________________________________________________________________________________________ function [handle] = myspectrogram(s, fs, T, w, nfft, Slim, alpha, cmap, cbar, type) %__________________________________________________________________________________________________________________ % VALIDATE INPUTS, SET DEFAULTS switch nargin case 1, type='per'; cbar=false; cmap='default'; alpha=false; Slim=[-65,-1]; w=@hamming; T=[18,1]; nfft=1024; fs=8000; case 2, type='per'; cbar=false; cmap='default'; alpha=false; Slim=[-65,-1]; w=@hamming; T=[20,1]; nfft=4096; case 3, type='per'; cbar=false; cmap='default'; alpha=false; Slim=[-65,-1]; w=@hamming; T=[18,1]; case 4, type='per'; cbar=false; cmap='default'; alpha=false; Slim=[-65,-1]; w=@hamming; case 5, type='per'; cbar=false; cmap='default'; alpha=false; Slim=[-65,-1]; case 6, type='per'; cbar=false; cmap='default'; alpha=false; case 7, type='per'; cbar=false; cmap='default'; case 8, type='per'; cbar=false; case 9, type='per'; case 10 otherwise, error('Invalid number of input arguments.'); end %__________________________________________________________________________________________________________________ % DECLARE VARIABLES if(isstr(s)), [s, fs] = audioread(s); end; % read audio data from file Tw = T(1); % frame width (ms) Ts = T(2); % frame shift (ms) Nw = round(fs*Tw*0.001); % frame width (samples) Ns = round(fs*Ts*0.001); % frame shift (samples) N = length(s); % length of speech signal (samples) Smin = Slim(1); % lower normalized dynamic range limit Smax = Slim(2); % upper normalized dynamic range limit if(isstr(w)), w = str2func(w); end; % obtain window function handle from string input %__________________________________________________________________________________________________________________ % SPEECH PREPROCESSING if(islogical(alpha) && alpha), s = filter([1 -0.95],1,s); % apply a typical preemphasis filter elseif(~islogical(alpha)) s = filter(alpha,1,s); end; % apply custom preemphasis filter %__________________________________________________________________________________________________________________ % GET SPECTROGRAM DATA [S,F,T] = spectrogram(s,w(Nw).',Nw-Ns,nfft,fs); % MATLAB's new spectrogram function % [S,F,T] = specgram(s,nfft,fs,w(Nw).',Nw-Ns); % MATLAB's depreciated spectrogram function % [S,F,T] = toframes(s,w,T,fs,nfft,type); % Framing function, use this if you do not have the Signal Processing Toolbox %__________________________________________________________________________________________________________________ % SET DYNAMIC RANGE S = abs(S); % compute magnitude spectrum S = S/max(max(S)); % normalize magntide spectrum % S(S<eps) = eps; % prevent zero spectral magnitude values S = 20*log10(S); % compute power spectrum in dB %__________________________________________________________________________________________________________________ % PLOT AND LABEL RESULTS TT = T*1000; handle = imagesc(TT, F, S, [Smin Smax]); % handle = imagesc(TT, F, S, 'CDataMapping', 'direct'); axis('xy'); % axis([0 N/fs 0 fs/2]); axis([0 length(TT) 0 fs/2]); % xlabel('time (s)', 'FontSize', 8, 'FontWeight', 'n'); % ylabel('frequency (Hz)', 'FontSize', 8, 'FontWeight', 'n'); % set(gca,'YDir','normal', 'FontSize', 6); if(cbar), colorbar('FontSize',6); end %__________________________________________________________________________________________________________________ % DEFINE CUSTOM COLOR MAPS switch(lower(cmap)) case {'default'} colormap('jet'); map=colormap; colormap(1-map); otherwise, colormap(cmap); end %______________________________________________________________________________________________________________________ % % @author Kamil Wojcicki % @date April 2007 % @revision 001 % @brief Implements toframes part of analysis-modification-synthesis (AMS) framework %______________________________________________________________________________________________________________________ function [S,F,T] = toframes(s,w,T,fs,nfft,type) %__________________________________________________________________________________________________________________ % VALIDATE INPUTS switch nargin case 1, type='per'; nfft=1024; fs=8000; T=[32 32/8]; w={@hamming, @hamming}; case 2, type='per'; nfft=1024; fs=8000; T=[32 32/8]; case 3, type='per'; nfft=1024; fs=8000; case 4, type='per'; nfft=1024; case 5, type='per'; case 6 otherwise, error('Invalid number of input arguments.'); end %__________________________________________________________________________________________________________________ % DEFINE VARIABLES if(isstr(s)) [s, fs, nbits] = wavread(s); else, nbits=16; end; s = s(:).'; % s = s-mean(s); smax = max(abs(s))/0.999; s = s/smax; Tw = T(1); % frame length [ms] Ts = T(2); % frame frameshift [ms] N = round(fs*Tw*0.001); % frame length [samples] Z = round(fs*Ts*0.001); % frame shift [samples] D = mod(length(s), Z); % add N-D zeros to the end G = (ceil(N/Z)-1)*Z; % add G zeros to the beginning s = [zeros(1,G) s zeros(1,N-D)]; % zero pad signal to allow an integer number of segments ss = length(s); % length of the signal for processing t = [0:ss-1]/fs; % time vector M = ((ss-N)/Z)+1; % number of overlapping segments if(isstr(w)), w=str2func(w); end; wa = w(N).';