Audio Spectrograms

Since classic spectrograms [125] typically show log-magnitude intensity (dB) versus time and frequency, and since sound-pressure level in dB is roughly proportional to perceived loudness, at least at high levels [169,259,282], we can say that a classic spectrogram provides a reasonably good psychoacoustic display for sound, provided the window length has been chosen to be comparable to the ``integration time'' of the ear.

However, there are several ways we can improve the classic spectrogram to obtain more psychoacoustically faithful displays of perceived loudness versus time and frequency:

• Loudness perception is closer to linearly related to amplitude at low loudness levels.

• Since the STFT offers only one ``integration time'' (the window length), it implements a uniform bandpass filter bank--i.e., spectral samples are uniformly spaced and correspond to equal bandwidths. The window transform gives the shape of each effective bandpass filter in the frequency domain. The choice of window length determines the common time- and frequency-resolution at all frequencies. Figure 8.14 shows a frequency-response overlay of all 5 channel filters created by a length 5 DFT using a zero-phase rectangular window.

  In the ear, however, time resolution increases and frequency resolution decreases at higher frequencies. Thus, the ear implements a non-uniform filter bank, with wider bandwidths at higher frequencies. In the time domain, the integration time (effective ``window length'') becomes shorter at higher frequencies.

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Subsections

• Auditory Filter Banks
• Loudness Spectrogram
• Loudness Spectrogram Examples
  • Multiresolution STFT
  • Excitation Pattern
  • Nonuniform Spectral Resampling
  • Specific Loudness
  • Spectrograms Compared
  • Instantaneous, Short-Term, and Long-Term Loudness

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About the Author: Julius Orion Smith III
Julius Smith's background is in electrical engineering (BS Rice 1975, PhD Stanford 1983). He is presently Professor of Music and Associate Professor (by courtesy) of Electrical Engineering at Stanford's Center for Computer Research in Music and Acoustics (CCRMA), teaching courses and pursuing research related to signal processing applied to music and audio systems. See http://ccrma.stanford.edu/~jos/ for details.

please send me complete matlab code of project of "matlab based time and frequency analysis and spectrogram of real signal such as speech using short time fourier transform"