Yesterday I was looking into calculating fluctuation strength and playing around with some examples. Along the way I discovered how to create files that sound like police sirens. These are sounds with high fluctuation strength.

The Python code below starts with a carrier wave at fc = 1500 Hz. Not surprisingly, this frequency is near where hearing is most sensitive. Then this signal is modulated with a signal with frequency fm. This frequency determines the frequency of the fluctuations.
The slower example produced by the code below sounds like a police siren. The faster example makes me think more of an ambulance or fire truck. Next time I hear an emergency vehicle I’ll pay more attention.
If you use a larger value of the modulation index β and a smaller value of the modulation frequency fm you can make a sound like someone tuning a radio, which is no coincidence.
Here are the output audio files in .wav format: slow.wav, fast.wav
from scipy.io.wavfile import write
from numpy import arange, pi, sin
def f(t, f_c, f_m, beta):
# t = time
# f_c = carrier frequency
# f_m = modulation frequency
# beta = modulation index
return sin(2*pi*f_c*t - beta*sin(2*f_m*pi*t))
def to_integer(signal):
# Take samples in [-1, 1] and scale to 16-bit integers,
# values between -2^15 and 2^15 - 1.
return int16(signal*(2**15 - 1))
N = 48000 # samples per second
x = arange(3*N) # three seconds of audio
data = f(x/N, 1500, 2, 100)
write("slow.wav", N, to_integer(data))
data = f(x/N, 1500, 8, 100)
write("fast.wav", N, to_integer(data))
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