def segment_audio_files(filepath, segment_length, result_dir=RESULT_DIR):
''' From an input audio file, segments the file into segments of length segment_length, and outputs them as individual files to result_dir
Parameters:
filepath - the path to the input file
segment_length - the length of the segment to return, in seconds
result_dir - output path to write to '''
filename = os.path.split(filepath)[1]
afm = audiofile_manager(filepath, segment_length)
checkdir(RESULT_DIR)
cleandir(RESULT_DIR)
print "File in 5-minute chunks"
while afm.HasMoreData():
segment, index = afm.GetNextSegment()
outFile = "%s/%s-%d.wav" % (RESULT_DIR, filename[:-4], index)
print "%d %.3f%%" % (index, (index * afm.seg_length_samps / np.float(afm.afReader.numsamples()))*100 )
print "Writing %s..." % (outFile),
M.wavwrite(segment, outFile, afm.afReader.samplerate())
print "...done."
def segment_audio_files(filepath, segment_length, result_dir=RESULT_DIR):
''' From an input audio file, segments the file into segments of length segment_length, and outputs them as individual files to result_dir
Parameters:
filepath - the path to the input file
segment_length - the length of the segment to return, in seconds
result_dir - output path to write to '''
filename = os.path.split(filepath)[1]
afm = audiofile_manager(filepath, segment_length)
checkdir(RESULT_DIR)
cleandir(RESULT_DIR)
print "File in 5-minute chunks"
while afm.HasMoreData():
segment, index = afm.GetNextSegment()
outFile = "%s/%s-%d.wav" % (RESULT_DIR, filename[:-4], index)
print "%d %.3f%%" % (index,
(index * afm.seg_length_samps /
np.float(afm.afReader.numsamples())) * 100)
print "Writing %s..." % (outFile),
M.wavwrite(segment, outFile, afm.afReader.samplerate())
print "...done."
import mirlib.feature_extraction.eventDetect as ed
import mirlib.FFTParams as fftparams
from matplotlib.pylab import *
#inputfile = '../audio_files/GV02_A_Format4min.wav'
inputfile = '../audio_files/wburgShort.wav'
if not os.path.exists(inputfile):
raise Exception("FILE DOES NOT EXIST, TRY AGAIN")
[x, fs] = M.wavread(inputfile)
# FFT Parameters
N = 2048
hopDenom = 2
zp = 0
winfunc=np.hamming
fftParams = fftparams.FFTParams(fs, N, hopDenom, zp, winfunc)
#peaks = z.envelopeFollowEnergy(winLen,hopSize) # the old way
z = ed.onsetDetect(fftParams)
events = z.findEventLocations(x)
xConcat = x[(events)]
M.wavwrite(xConcat, "segs.wav", fs)
import os
import numpy as np
import marlib.matlab as M
import mirlib.feature_extraction.eventDetect as ed
import mirlib.FFTParams as fftparams
from matplotlib.pylab import *
#inputfile = '../audio_files/GV02_A_Format4min.wav'
inputfile = '../audio_files/wburgShort.wav'
if not os.path.exists(inputfile):
raise Exception("FILE DOES NOT EXIST, TRY AGAIN")
[x, fs] = M.wavread(inputfile)
# FFT Parameters
N = 2048
hopDenom = 2
zp = 0
winfunc = np.hamming
fftParams = fftparams.FFTParams(fs, N, hopDenom, zp, winfunc)
#peaks = z.envelopeFollowEnergy(winLen,hopSize) # the old way
z = ed.onsetDetect(fftParams)
events = z.findEventLocations(x)
xConcat = x[(events)]
M.wavwrite(xConcat, "segs.wav", fs)
