How get sound input from microphone in python, and process it on the fly?
Question:
Greetings,
I’m trying to write a program in Python which would print a string every time it gets a tap in the microphone. When I say ‘tap’, I mean a loud sudden noise or something similar.
I searched in SO and found this post: Recognising tone of the audio
I think PyAudio library would fit my needs, but I’m not quite sure how to make my program wait for an audio signal (realtime microphone monitoring), and when I got one how to process it (do I need to use Fourier Transform like it was instructed in the above post)?
Thank you in advance for any help you could give me.
Answers:
If you are using LINUX, you can use pyALSAAUDIO.
For windows, we have PyAudio and there is also a library called SoundAnalyse.
I found an example for Linux here:
#!/usr/bin/python
## This is an example of a simple sound capture script.
##
## The script opens an ALSA pcm for sound capture. Set
## various attributes of the capture, and reads in a loop,
## Then prints the volume.
##
## To test it out, run it and shout at your microphone:
import alsaaudio, time, audioop
# Open the device in nonblocking capture mode. The last argument could
# just as well have been zero for blocking mode. Then we could have
# left out the sleep call in the bottom of the loop
inp = alsaaudio.PCM(alsaaudio.PCM_CAPTURE,alsaaudio.PCM_NONBLOCK)
# Set attributes: Mono, 8000 Hz, 16 bit little endian samples
inp.setchannels(1)
inp.setrate(8000)
inp.setformat(alsaaudio.PCM_FORMAT_S16_LE)
# The period size controls the internal number of frames per period.
# The significance of this parameter is documented in the ALSA api.
# For our purposes, it is suficcient to know that reads from the device
# will return this many frames. Each frame being 2 bytes long.
# This means that the reads below will return either 320 bytes of data
# or 0 bytes of data. The latter is possible because we are in nonblocking
# mode.
inp.setperiodsize(160)
while True:
# Read data from device
l,data = inp.read()
if l:
# Return the maximum of the absolute value of all samples in a fragment.
print audioop.max(data, 2)
time.sleep(.001)
…and when I got one how to process it (do I need to use Fourier Transform like it was instructed in the above post)?
If you want a “tap” then I think you are interested in amplitude more than frequency. So Fourier transforms probably aren’t useful for your particular goal. You probably want to make a running measurement of the short-term (say 10 ms) amplitude of the input, and detect when it suddenly increases by a certain delta. You would need to tune the parameters of:
- what is the “short-term” amplitude measurement
- what is the delta increase you look for
- how quickly the delta change must occur
Although I said you’re not interested in frequency, you might want to do some filtering first, to filter out especially low and high frequency components. That might help you avoid some “false positives”. You could do that with an FIR or IIR digital filter; Fourier isn’t necessary.
I know it’s an old question, but if someone is looking here again… see https://python-sounddevice.readthedocs.io/en/0.4.1/index.html .
It has a nice example "Input to Ouput Pass-Through" here https://python-sounddevice.readthedocs.io/en/0.4.1/examples.html#input-to-output-pass-through .
… and a lot of other examples as well …
Greetings,
I’m trying to write a program in Python which would print a string every time it gets a tap in the microphone. When I say ‘tap’, I mean a loud sudden noise or something similar.
I searched in SO and found this post: Recognising tone of the audio
I think PyAudio library would fit my needs, but I’m not quite sure how to make my program wait for an audio signal (realtime microphone monitoring), and when I got one how to process it (do I need to use Fourier Transform like it was instructed in the above post)?
Thank you in advance for any help you could give me.
If you are using LINUX, you can use pyALSAAUDIO.
For windows, we have PyAudio and there is also a library called SoundAnalyse.
I found an example for Linux here:
#!/usr/bin/python
## This is an example of a simple sound capture script.
##
## The script opens an ALSA pcm for sound capture. Set
## various attributes of the capture, and reads in a loop,
## Then prints the volume.
##
## To test it out, run it and shout at your microphone:
import alsaaudio, time, audioop
# Open the device in nonblocking capture mode. The last argument could
# just as well have been zero for blocking mode. Then we could have
# left out the sleep call in the bottom of the loop
inp = alsaaudio.PCM(alsaaudio.PCM_CAPTURE,alsaaudio.PCM_NONBLOCK)
# Set attributes: Mono, 8000 Hz, 16 bit little endian samples
inp.setchannels(1)
inp.setrate(8000)
inp.setformat(alsaaudio.PCM_FORMAT_S16_LE)
# The period size controls the internal number of frames per period.
# The significance of this parameter is documented in the ALSA api.
# For our purposes, it is suficcient to know that reads from the device
# will return this many frames. Each frame being 2 bytes long.
# This means that the reads below will return either 320 bytes of data
# or 0 bytes of data. The latter is possible because we are in nonblocking
# mode.
inp.setperiodsize(160)
while True:
# Read data from device
l,data = inp.read()
if l:
# Return the maximum of the absolute value of all samples in a fragment.
print audioop.max(data, 2)
time.sleep(.001)
…and when I got one how to process it (do I need to use Fourier Transform like it was instructed in the above post)?
If you want a “tap” then I think you are interested in amplitude more than frequency. So Fourier transforms probably aren’t useful for your particular goal. You probably want to make a running measurement of the short-term (say 10 ms) amplitude of the input, and detect when it suddenly increases by a certain delta. You would need to tune the parameters of:
- what is the “short-term” amplitude measurement
- what is the delta increase you look for
- how quickly the delta change must occur
Although I said you’re not interested in frequency, you might want to do some filtering first, to filter out especially low and high frequency components. That might help you avoid some “false positives”. You could do that with an FIR or IIR digital filter; Fourier isn’t necessary.
I know it’s an old question, but if someone is looking here again… see https://python-sounddevice.readthedocs.io/en/0.4.1/index.html .
It has a nice example "Input to Ouput Pass-Through" here https://python-sounddevice.readthedocs.io/en/0.4.1/examples.html#input-to-output-pass-through .
… and a lot of other examples as well …