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### Avisoft-SASLab Pro Tutorial
When a spectrogram is generated, several parameters
(FFT-Length, Frame size, Window type and Overlap) selected from the
"Analyze/Spectrogram Parameters" command can be modified in order to
get the desired time / frequency resolution and bandwidth of the
spectrogram.
The digital spectrogram is a matrix of
amplitudes. Each amplitude of that matrix corresponds to a single
pixel (picture element) of the spectrogram image. The height of such
a pixel is the frequency resolution [Hz]. The width of a pixel is
the temporal resolution [s] displayed in the spectrogram parameters
dialog. The total height of the spectrogram matrix is equal to one
half of the FFT-Length. The spectrogram bandwidth is not the same as
the frequency resolution of the digital spectrogram matrix. The
bandwidth is usually higher than the resolution and is influenced by
the frame size and the window type.
Effect of spectrogram
parameters to spectrogram bandwidth and time constant
Parameter modification |
bandwidth |
time constant |
FFT-Length increased |
decreased |
increased |
Frame[%] decreased |
increased |
decreased |
Sampling frequency decreased |
decreased |
increased |
The window
type also influences the bandwidth. The smallest bandwidth is
realized with the rectangular window. Because of the unacceptable
leakeage effect (bad selectivity and spurious frequency components
depending on the signal frequency the rectangualar and Bartlett
window should not be used for standard applications. So the lowest
bandwidth can be achieved with the Hamming window. The largest
bandwidth gives the FlatTop window. The following list is sorted by
ascending bandwidths:
(Rectangular, Bartlett), Hamming,
Hann, Blackman, Gauss 3.0, Kaiser-Bessel, FlatTop
In
general, narrow bandwidths should be chosen if the signal to be
analyzed does not have quick frequency modulations and if there is
no important information in the time domain. In contrast, wide
bandwidths should be chosen if there is any remarkable frequency
modulation or if there are important temporal patterns.
The
examples of a Chaffinch (*Fringilla coelebs*) song shown here
were produced with different spectrogram parameters. The following
parameters are the same for all spectrograms:
- FFT-Length = 512
- Overlap = 99,21%
- Sampling frequency = 22.05 kHz
These settings will
produce a temporal resolution of 0.36 ms. The y-scale is limited to
8 kHz (File/Export Parameters) because there are no signals beyond
that frequency. Usually the spectrogram would show signals up to
11.025 kHz (1/2 * 22.05 kHz).
Frame[%] = 100, Window = Hamming, Bandwidth = 56 Hz, Time
constant = 18 ms
Because of the swift frequency changes and
the short song elements in this song, the narrow bandwidth of 56 Hz
is too small.
Frame[%] = 50, Window = Hamming, Bandwidth = 112 Hz, Time
constant = 9 ms
Frame[%] = 50, Window = FlatTop, Bandwidth = 324 Hz, Time
constant = 3 ms
These settings are the most appropriate for
this song. It is a good compromise between time constant and
bandwidth, because the frequency modulation at the end of the last
element can be seen clearly and the pitch measurements are still
acceptable.
Frame[%] = 25, Window = FlatTop, Bandwidth = 648 Hz, Time
constant = 1.5 ms
These settings may also be acceptable as
those above.
Frame[%] = 12.5, Window = FlatTop, Bandwidth = 1295 Hz, Time
constant = 0.8 ms
The bandwidth is too high for this kind of
signal.
This
display shows the same section analyzed with the
Analyze/One-dimensional Transformation/Instantaneous frequency
command. This kind of analysis does not have the tradeoff between time constant and bandwidth. Both frequency and
temporal properties can be measured very precise. However, it does
only work properly for signals without any harmonics (pure tone
whistles). There is another analysis option (Analyze/One-dimensional
Transformation/Zero-crossing analysis), which provides simliar
results, except, that the precision is a little bit lower. However,
the zero-crossing analysis is not limited in duration as the
instantaneous frequency command. Additionally the zero-crossing
analysis is much more faster.
The next example is the song
of a M ountain Chickadee (*Parus gambeli*) which does not have
any frequency modulation within the clearly separated elements.
Frame[%] = 100, Window = Hamming, Bandwidth = 56
Hz, Time constant = 18 ms
This narrow bandwidth spectrogram
is appropriate to show the properties of this song, because there
are no major frequency modulations and the inter-element duration is
relatively long.
Frame[%] = 50, Window = FlatTop, Bandwidth = 324 Hz, Time
constant = 3 ms
This wide bandwidth spectrogram is also
acceptable, but the precision of pitch measurements is limited.
However, if you are interested in the reverberation visible at the
end of each element, these settings may be more useful to extract
the temporal properties of the reverberation.
For analyzing
low frequency signals it may be useful to decrease the sampling
frequency of the sound card. Sampling frequency conversion can also
be done subsequently by using the command Edit/Format/Sampling
Frequency Conversion...
Sampling frequency = 11025 Hz, FFT-length = 256, Resolution
= 43 Hz, Overlap = 50%
Sampling frequency = 1000 Hz, FFT-length = 256, Resolution =
3 Hz, Overlap = 96.87% | |