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 f_c = 1500 Hz. Not surprisingly, this frequency is near where hearing is most sensitive. Then this signal is modulated with a signal with frequency f_m. 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 f_m, 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(data*(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))

Related Posts

• Analyzing an FM signal
• Energy in FM signals