mfcc.zip_matlab语音识别_voice MFCC matlab_语音识别

function m = melfb(p, n, fs) % MELFB Determine matrix for a mel-spaced filterbank % % Inputs: p number of filters in filterbank % n length of fft % fs sample rate in Hz % % Outputs: x a (sparse) matrix containing the filterbank amplitudes % size(x) = [p, 1+floor(n/2)] % % Usage: For example, to compute the mel-scale spectrum of a % colum-vector signal s, with length n and sample rate fs: % % f = fft(s); % m = melfb(p, n, fs); % n2 = 1 + floor(n/2); % z = m * abs(f(1:n2)).^2; % % z would contain p samples of the desired mel-scale spectrum % % To plot filterbanks e.g.: % % plot(linspace(0, (12500/2), 129), melfb(20, 256, 12500)'), % title('Mel-spaced filterbank'), xlabel('Frequency (Hz)'); f0 = 700 / fs; fn2 = floor(n/2); lr = log(1 + 0.5/f0) / (p+1); % convert to fft bin numbers with 0 for DC term bl = n * (f0 * (exp([0 1 p p+1] * lr) - 1)); b1 = floor(bl(1)) + 1; b2 = ceil(bl(2)); b3 = floor(bl(3)); b4 = min(fn2, ceil(bl(4))) - 1; pf = log(1 + (b1:b4)/n/f0) / lr; fp = floor(pf); pm = pf - fp; r = [fp(b2:b4) 1+fp(1:b3)]; c = [b2:b4 1:b3] + 1; v = 2 * [1-pm(b2:b4) pm(1:b3)]; m = sparse(r, c, v, p, 1+fn2);