def main():
n_people = 3
grouppath = "./Dropbox/group/"
ngroup = dircount(grouppath)
SR = speaker_recognition(
n_people, os.path.join(grouppath, "group{}".format(ngroup - 1)))
index = SR.transform()
fname = os.path.join(
grouppath, "group{}/target/aux_{}.wav".format(ngroup - 1,
int(index[0])))
afps, data = cis.wavread(fname)
x = np.array(data)
for i in range(1, n_people):
fname = os.path.join(
grouppath,
"group{}/target/ilrma_{}.wav".format(ngroup - 1, int(index[1])))
_, data = cis.wavread(fname)
x = np.vstack([x, data.astype(float)])
fname = os.path.join(grouppath,
"group{}/target/input.wav".format(ngroup - 1))
_, data = cis.wavread(fname)
sepvoice = x
rawvoice = np.array(data, dtype=np.float32)
vfname = "./Video/group/group{}/input.avi".format(ngroup - 1)
outfile = "./Video/group/group{}/output".format(ngroup - 1)
recog = FacialRecog(vfname, rawvoice[:, 0], sepvoice, afps, outfile)
recog.main()
def generator_from_files(self, file_path1, file_path2, chunk_size=8000):
"""
For testing 2-channel audio translation
:param file_path1: wav file containing signal from the first microphone
:param file_path2: wav file containing signal from the second microphone
:param chunk_size: sequence size used for processing
:return:y[0] -separated 1st channel, y[1] -2nd channel
"""
rate1, data1 = cis.wavread(file_path1)
rate2, data2 = cis.wavread(file_path2)
#rate1, data1 = cis.wavread('./data/rssd_A.wav')
#rate2, data2 = cis.wavread('./data/rssd_B.wav')
if rate1 != rate2:
raise ValueError('Sampling_rate_Error')
fs = rate1
#for ind in range(0, data1.shape[0] - chunk_size, chunk_size):
for ind in range(0, data1.shape[0] - chunk_size, chunk_size):
start_time = time.time()
try:
x = np.array(
[data1[ind:ind + chunk_size], data2[ind:ind + chunk_size]],
dtype=np.float32)
y = AuxIVA(x, sample_freq=fs, beta=0.3, nchannel=2).auxiva()
print("--- %s seconds ---" % (time.time() - start_time))
except np.linalg.LinAlgError as err:
if 'Singular matrix' in str(err):
# error handling block, probably continue
print("Singular matrix")
yield np.array([0, 1])
else:
break
yield y
def main():
grouppath = "./Dropbox/group"
ngroup = dircount(grouppath)
dirname = os.path.join(grouppath, "group{}/target".format(ngroup-1))
fs, data = cis.wavread(os.path.join(dirname, "input.wav"))
x = np.array([data[:, 0], data[:, 1], data[:, 2]], dtype=np.float32)
y = ILRMA(x, fs, 2, 200).ilrma()
cis.wavwrite(os.path.join(dirname, "ilrma_0.wav"), fs, y[0])
cis.wavwrite(os.path.join(dirname, "ilrma_1.wav"), fs, y[1])
cis.wavwrite(os.path.join(dirname, "ilrma_2.wav"), fs, y[2])
def add_vibrato(file, fv, p=0.1):
"""
与えられた音源にビブラートをかける関数
file(wav): ビブラートをかけるwavfileを指定
fv(int): 周波数がfvの正弦波の形で変動する
p(int): 元の音源の周波数をa,上下させる周波数をbとした時,p=b/aとしたもの
元の音源の周波数の何倍変動させるか指定する
"""
y,fs = cis.wavread(file)
t = np.arange(0, y.shape[0]/fs, 1/fs)
g = t - p/(2*np.pi*fv)*np.cos(2*np.pi*fv*t)
passing = np.argwhere(g > t[-1])
if passing.size != 0:
g = g[:passing[0, 0]]
mody = np.interp(g, t, y)
cis.audioplay(mody, fs)
fy1 = max(0, y-h//2)
fy2 = min(y+h+h//2, src.shape[0])
output = output // 3
output[fy1:fy2,fx1:fx2,:] *= 3
return output
def __audio_concat(self):
sft = self.nframe // (self.M+2) * self.afps // self.vfps
for m in range(self.M+2):
if m < 1:
output = self.rawvoice[sft*m:sft*(m+1)]
elif m > self.M:
output = np.hstack((output, self.rawvoice[sft*m:]))
else:
output = np.hstack((output, self.sepvoice[m-1, sft*m:sft*(m+1)]))
return output
if __name__ == "__main__":
rate1, data1 = cis.wavread('./samples/group/auxiva_2.wav')
rate2, data2 = cis.wavread('./samples/group/auxiva_1.wav')
rate3, data3 = cis.wavread('./samples/group/auxiva_0.wav')
rate4, data4 = cis.wavread('./samples/group/output.wav')
sepvoice = np.array([data1, data2, data3], dtype=np.float32)
rawvoice = np.array(data4, dtype=np.float32)
recog = FacialRecog("samples/WIN_20190515_18_14_38_Pro.mp4", rawvoice[:,0], sepvoice, rate1, "samples/aaa")
recog.main()
import numpy as np
import cis
from AuxIVA import AuxIVA
import time
rate1, data1 = cis.wavread('./data/rssd_A.wav')
rate2, data2 = cis.wavread('./data/rssd_B.wav')
#rate3, data3 = cis.wavread('./samples/mixdata/mix3.wav')
if rate1 != rate2: #or rate2 != rate3:
raise ValueError('Sampling_rate_Error')
fs = rate1
print(fs)
print(data1.shape)
start_time = time.time()
x = np.array([data1[:10000], data2[:10000]], dtype=np.float32)
y = AuxIVA(x, sample_freq=fs, beta=0.3, nchannel=2).auxiva()
print("--- %s seconds ---" % (time.time() - start_time))
import numpy as np
import sys
import cis
import scipy.io.wavfile as wf
from IVA import IVA
from sound_mixing import Preprocessing
#prepare data
rate1, data1 = cis.wavread('./samples/music1.wav')
rate2, data2 = cis.wavread('./samples/music2.wav')
rate3, data3 = cis.wavread('./samples/music3.wav')
if rate1 != rate2 or rate2 != rate3:
raise ValueError('Sampling_rate_Error')
fs = rate1
x = np.array([data1, data2, data3], dtype=np.float32)
y = IVA(x, fs).iva()
cis.wavwrite('./samples/iva_1_out.wav', fs, y[0])
cis.wavwrite('./samples/iva_2_out.wav', fs, y[1])
cis.wavwrite('./samples/iva_3_out.wav', fs, y[2])