2. spectrogram
A spectrogram is a representation of how the frequency content of a signal changes with time.
Time is displayed along the x-axis, frequency along the y-axis, and the amount of energy in the
signal at any given time and frequency is displayed as a level of grey. During regions of silence,
and at frequency regions where there is little energy, the spectrogram appears white; dark
regions indicate areas of energy - caused for example by vocal fold closures, harmonics, or
formant vibration in a speech signal.
4. Spectrogram study
There are two types of spectrogram for speech study: one which emphasizes the frequency aspects
by using long signal sections or narrow analysis filters, and
one which emphasizes the temporal aspects by using short signal sections or wide analysis filters.
Narrow-band spectrograms are convenient for investigating characteristics of the source: they show
the harmonics of the vocal fold vibration for example.
Wide-band spectrograms are convenient for investigating characteristics of the vocal tract filter:
they highlight the vocal tract resonances (formants) by showing how they continue to vibrate after
a vocal fold pulse has passed through.
5. Spectrogram-wide and narrow band
Spectrogram: Graph of the energy content of a signal expressed as
function of frequency and time. Graph of a signal in which the vertical
axis is frequency, the horizontal axis is time, and amplitude is shown on
a grey-scale.
Wide-band spectrogram: A spectrogram produced using an analysis
scheme which emphasises temporal changes in the signal: with short-
time spectrum calculations (about 3ms) or highly damped analysis
filters (about 300Hz).
Narrow-band spectrogram: A spectrogram produced using an analysis
scheme which emphasises frequency changes in the signal: with long-
time spectrum calculations (about 20ms) or lightly damped analysis
filters (about 45Hz).
6. spectrogram
A spectrogram is built from a sequence of spectra by
stacking them together in time and by compressing the
amplitude axis into a 'contour map' drawn in a grey
scale. The final graph has time along the horizontal
axis, frequency along the vertical axis, and the
amplitude of the signal at any given time and frequency
is shown as a grey level. Conventionally, black is used to
signal the most energy, while white is used to signal the
least
9. Spectra of dynamic signals
like many real world signals, speech changes in quality with time. But so far
the only spectral analysis we have performed has assumed that the signal is
stationary: that it has constant quality. We need a new kind of analysis for
dynamic signals. A suitable analogy is that we have spectral ‘snapshots’ when
what we really want is a spectral ‘movie’. Just like a real movie is made up
from a series of still frames, we can display the spectral properties of a
changing signal through a series of spectral snapshots.
