Created
June 17, 2019 15:08
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#!/usr/local/bin/python3 | |
from pydub import AudioSegment | |
from pyAudioAnalysis import audioBasicIO as aIO | |
from pyAudioAnalysis import audioSegmentation as aS | |
import sys | |
import numpy | |
from scipy.io import wavfile | |
from scipy.signal import fftconvolve | |
def usage(): | |
sys.exit("Usage: double_ender_sync master.wav sync.wav sync2.wav ...") | |
if len(sys.argv) < 3: | |
usage() | |
master = AudioSegment.from_wav(sys.argv[1]) | |
master = master.set_channels(1) | |
files_to_sync = sys.argv[2:] | |
filenumber = 0 | |
for sync_filename in files_to_sync: | |
print("Syncing %s to %s" %(sync_filename,sys.argv[1])) | |
filenumber = filenumber + 1 | |
sync = AudioSegment.from_file(sync_filename) | |
sync = sync.set_channels(1) | |
# First reduce file sizes by only looking at relevant areas | |
needle_abs_index = 0 | |
offset = abs(len(sync)-len(master)) * 1.05 | |
# If there's less then 5 minutes difference, give us a bit more headroom. | |
if (offset<5*60*1000): | |
offset = 5*60*1000 | |
search_area = master[:offset*2] | |
sample_area = sync[offset:10*60*1000+offset] | |
needle_abs_index = offset | |
search_area.export("search_area.wav", format="wav") | |
sample_area.export("sample_area.wav", format="wav") | |
# Segment sample area into speech bits and use first one to locate within | |
[Fs, x] = aIO.readAudioFile("sample_area.wav") | |
segments = aS.silenceRemoval(x, Fs, 0.05, 0.05, 1.0, 0.8, False) | |
for timeidx in segments: | |
start = timeidx[0] * 1000 | |
end = timeidx[1] * 1000 | |
needle_abs_index = needle_abs_index + start | |
if (end-start>2*1000): | |
needle = sample_area[start:end] | |
print("Found a needle") | |
needle.export("needle.wav", format="wav") | |
break | |
# Search code adapted from wavgrep.py (https://gist.github.com/patrakov/8a8095721ee81d49f16c) | |
needle_rate, needle = wavfile.read("needle.wav") | |
haystack_rate, haystack = wavfile.read("search_area.wav") | |
if needle_rate != haystack_rate: | |
sys.exit("Sample rates are not the same") | |
needle = numpy.array(needle, dtype=numpy.float64) | |
needle_len = len(needle) | |
haystack = numpy.array(haystack, dtype=numpy.float64) | |
haystack_len = len(haystack) | |
needle_norm = needle.dot(needle) | |
if needle_norm < 1000.0: | |
sys.exit("The needle is almost silent") | |
haystack_squared = numpy.hstack(([0.0], haystack * haystack)) | |
haystack_cum_norm = numpy.cumsum(haystack_squared) | |
haystack_norm_at = haystack_cum_norm[needle_len:haystack_len + 1] - haystack_cum_norm[0:haystack_len + 1 - needle_len] | |
correlation_at = fftconvolve(haystack, needle[::-1], mode='valid') | |
difference_norm_at = haystack_norm_at + needle_norm - 2 * correlation_at | |
cos2phi_at = correlation_at * correlation_at / (haystack_norm_at + 0.000001) / needle_norm | |
at = numpy.argmin(difference_norm_at) | |
# Calculate diffs and write synced file. | |
time_offset = abs(needle_abs_index-(at/haystack_rate*1000)) | |
print("Absolute needle pos: %d" % needle_abs_index) | |
print("The needle starts at ms: %d" % round(at/haystack_rate*1000)) | |
print("Time Offset: %d seconds" % round(time_offset/1000)) | |
synced = sync[time_offset:] | |
synced.export("synced-track%d.wav" % filenumber, format="wav") | |
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