def split_wav(wav_file, ref_file, is_save=False, dir_name="split"):
from scikits.audiolab import formatinfo as format
import scikits.audiolab as audiolab
import shutil
fr = audiolab.sndfile(wav_file, "read")
n_channels = fr.get_channels()
fmt = format("wav", fr.get_encoding())
fs = fr.get_samplerate()
if is_save:
shutil.rmtree(dir_name, ignore_errors=True)
shutil.os.mkdir(dir_name)
slices = dict()
with open(ref_file, "r") as ref_read:
for i, line in enumerate(ref_read.readlines()):
fields = line.strip().split(" ")
assert len(fields) == 3
begin = int(fields[0])
end = int(fields[1])
word = fields[2]
fr.seek(begin)
sli = fr.read_frames(end - begin + 1)
if not slices.has_key(word):
slices[word] = []
# if(len(sli) == 1):
# print word, line
slices[word].append(sli)
if is_save:
path = shutil.os.path.join(dir_name, str(i) + "-" + word + ".wav")
afile = audiolab.sndfile(path, "write", fmt, n_channels, fs)
afile.write_frames(sli, len(sli))
afile.close()
return slices
from tempfile import mkstemp
from os import remove
import numpy as N
from scikits.audiolab import formatinfo as format
import scikits.audiolab as audiolab
# Create a temp file in the system temporary dir, and always remove
# it at the end
cd, filename = mkstemp('tmptest.wav')
try:
fmt = format('wav', 'pcm24')
nchannels = 2
fs = 44100
afile = audiolab.sndfile(filename, 'write', fmt, nchannels, fs)
# Create a stereo white noise, with Gaussian distribution
tmp = 0.1 * N.random.randn(1000, nchannels)
# Write the first 500 frames of the signal
# Note that the write_frames method uses tmp's numpy dtype to determine how
# to write to the file; sndfile also converts the data on the fly if necessary
afile.write_frames(tmp, 500)
afile.close()
# Let's check that the written file has the expected meta data
afile = audiolab.sndfile(filename, 'read')
assert (afile.get_samplerate() == fs)
assert (afile.get_channels() == nchannels)
from scikits.audiolab import formatinfo as format
f = format('aiff', 'ulaw')
print f
f = format('ircam', 'float32')
print f
from tempfile import mkstemp
from os import remove
import numpy as N
from scikits.audiolab import formatinfo as format
import scikits.audiolab as audiolab
# Create a temp file in the system temporary dir, and always remove
# it at the end
cd, filename = mkstemp('tmptest.wav')
try:
fmt = format('wav', 'pcm24')
nchannels = 2
fs = 44100
afile = audiolab.sndfile(filename, 'write', fmt, nchannels, fs)
# Create a stereo white noise, with Gaussian distribution
tmp = 0.1 * N.random.randn(1000, nchannels)
# Write the first 500 frames of the signal
# Note that the write_frames method uses tmp's numpy dtype to determine how
# to write to the file; sndfile also converts the data on the fly if necessary
afile.write_frames(tmp, 500)
afile.close()
# Let's check that the written file has the expected meta data
afile = audiolab.sndfile(filename, 'read')
assert(afile.get_samplerate() == fs)
assert(afile.get_channels() == nchannels)