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Voice mixer
After many hours of research I finally saw that a fairly simple approach to Overlap/Add can be used to implement continuous FFT filtering. Here is my version of the original SoundDevice wire.py that has continuous FFT with no glitches (I think):
#!/usr/bin/env python3
"""Pass input directly to output.
https://app.assembla.com/spaces/portaudio/git/source/master/test/patest_wire.c
"""
import argparse
import sounddevice as sd
import numpy # Make sure NumPy is loaded before it is used in the callback
assert numpy # avoid "imported but unused" message (W0611)
def int_or_str(text):
"""Helper function for argument parsing."""
try:
return int(text)
except ValueError:
return text
parser = argparse.ArgumentParser(add_help=False)
parser.add_argument(
'-l', '--list-devices', action='store_true',
help='show list of audio devices and exit')
args, remaining = parser.parse_known_args()
if args.list_devices:
print(sd.query_devices())
parser.exit(0)
parser = argparse.ArgumentParser(
description=doc,
formatter_class=argparse.RawDescriptionHelpFormatter,
parents=[parser])
parser.add_argument(
'-i', '--input-device', type=int_or_str,
help='input device (numeric ID or substring)')
parser.add_argument(
'-o', '--output-device', type=int_or_str,
help='output device (numeric ID or substring)')
parser.add_argument(
'-c', '--channels', type=int, default=2,
help='number of channels')
parser.add_argument('--dtype', help='audio data type')
parser.add_argument('--samplerate', type=float, help='sampling rate')
parser.add_argument('--blocksize', type=int, help='block size', default=1024)
parser.add_argument('--latency', type=float, help='latency in seconds')
args = parser.parse_args(remaining)
first = True
parser.parse_args() # needed to prevent blocksize from being 'none' in overlap computation
blocksize = args.blocksize
overlap = blocksize // 2
inbuffer = numpy.zeros([blocksize * 3, 2])
outbuffer = numpy.zeros([blocksize + overlap * 2, 2])
timedata = numpy.zeros([blocksize + overlap * 2, 2])
channel = numpy.zeros([blocksize + overlap * 2]) # needs to be power of 2
mask = numpy.hanning(blocksize + overlap * 2) # blackman is another possibility
def callback(indata, outdata, frames, time, status):
global first, blocksize, overlap, inbuffer, outbuffer, mask, timedata, channel
if status:
print(status)
# because of buffering, we introduce a delay of 3 reads before output
# is clean.
inbuffer[blocksize * 2:] = indata # append to inbuffer
timedata = inbuffer[blocksize - overlap:blocksize * 2 + overlap, :]
# expand with loop to do all channels
# replace timedata with inbuffer[blocksize - overlap:blocksize * 2 + overlap, :]?
channel[:] = timedata[:, 0] * mask
# do fft
freqdata = numpy.fft.rfft(channel)
# do filtering here
channel = numpy.fft.irfft(freqdata)
outbuffer[:, 0] += channel
inbuffer[:-blocksize] = inbuffer[blocksize:] # left shift inbuffer
inbuffer[-blocksize:] = 0 # not really needed for input buffer as replacement is done
outbuffer[:-overlap] = outbuffer[overlap:] # left shift outbuffer
outbuffer[-overlap:] = 0 # here, we do a add to the overlap and this zeroed area
outdata[:] = outbuffer[:blocksize]
first = False
try:
with sd.Stream(device=(args.input_device, args.output_device),
samplerate=args.samplerate, blocksize=args.blocksize,
dtype=args.dtype, latency=args.latency,
channels=args.channels, callback=callback):
print('#' * 80)
print('press Return to quit')
print('#' * 80)
input()
except KeyboardInterrupt:
parser.exit('')
except Exception as e:
parser.exit(type(e).name + ': ' + str(e))
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