Classic SpectrogramsThe spectrogram is a basic tool in audio spectral analysis and other applications. It has been used extensively in speech analysis . The spectrogram can be defined as an intensity plot (usually on a log scale, such as dB) of the Short-Time Fourier Transform (STFT) magnitude.8.4 As defined in the previous section, the STFT is simply a sequence of FFTs of windowed data segments, where the windows are allowed to overlap in time, typically by at least 50% . Parameters of the spectrogram include the
- window length ,
- window type (Hamming, Kaiser, etc.),
- hop-size , and
- FFT length .
The spectrogram is an important representation of audio data because human hearing is based on a kind of real-time spectrogram encoded by the cochlea of the inner ear . The spectrogram has been used extensively in the field of computer music as a guide during the development of sound synthesis algorithms. When working with an appropriate synthesis model, matching the spectrogram often corresponds to matching the sound extremely well. In fact, spectral modeling synthesis (SMS) is based on synthesizing the short-time spectrum directly by some means (see §10.4) .
Spectrogram of Speech7.2. It was generated using the Matlab code displayed in Fig.7.3. The function spectrogram is listed in §F.3. The spectrogram is computed as a sequence of FFTs of windowed data segments. The spectrogram is plotted within spectrogram using imagesc.
[y,fs,bits] = wavread('SpeechSample.wav'); soundsc(y,fs); % Let's hear it % for classic look: colormap('gray'); map = colormap; imap = flipud(map); M = round(0.02*fs); % 20 ms window is typical N = 2^nextpow2(4*M); % zero padding for interpolation w = hamming(M); spectrogram(y,N,fs,w,-M/8,1,60); title('Speech Sample Spectrogram'); colormap(imap);
- The harmonics should be resolved.
- Pitch and formant variations should be closely followed.
The Short-Time Fourier Transform