def test_ubm_var_channel():
ubm = GMM.load('model/ubm.mixture-32.person-20.immature.model')
train_duration = 8.
nr_test = 5
test_duration = 3.
audio_files = ['xinyu.vad.wav', 'wyx.wav']
X_train, y_train, X_test, y_test = [], [], [], []
for audio_file in audio_files:
fs, signal = wavfile.read(audio_file)
signal = monotize_signal(signal)
train_len = int(fs * train_duration)
test_len = int(fs * test_duration)
X_train.append(mix_feature((fs, signal[:train_len])))
y_train.append(audio_file)
for i in range(nr_test):
start = random.randint(train_len, len(signal) - test_len)
X_test.append(mix_feature((fs, signal[start:start + train_len])))
y_test.append(audio_file)
gmmset = GMMSet(32, ubm=ubm)
gmmset.fit(X_train, y_train)
y_pred = gmmset.predict_with_reject(X_test)
for i in xrange(len(y_pred)):
print y_test[i], y_pred[i], '' if y_test[i] == y_pred[i] else 'wrong'
for imposter_audio_file in map(lambda x: 'test-{}.wav'.format(x),
range(5)):
fs, signal = wavfile.read(imposter_audio_file)
signal = monotize_signal(signal)
imposter_x = mix_feature((fs, signal))
print gmmset.predict_one_with_rejection(imposter_x)
def test_ubm_var_channel():
ubm = GMM.load('model/ubm.mixture-32.person-20.immature.model')
train_duration = 8.
nr_test = 5
test_duration = 3.
audio_files = ['xinyu.vad.wav', 'wyx.wav']
X_train, y_train, X_test, y_test = [], [], [], []
for audio_file in audio_files:
fs, signal = wavfile.read(audio_file)
signal = monotize_signal(signal)
train_len = int(fs * train_duration)
test_len = int(fs * test_duration)
X_train.append(mix_feature((fs, signal[:train_len])))
y_train.append(audio_file)
for i in range(nr_test):
start = random.randint(train_len, len(signal) - test_len)
X_test.append(mix_feature((fs, signal[start:start+train_len])))
y_test.append(audio_file)
gmmset = GMMSet(32, ubm=ubm)
gmmset.fit(X_train, y_train)
y_pred = gmmset.predict_with_reject(X_test)
for i in xrange(len(y_pred)):
print y_test[i], y_pred[i], '' if y_test[i] == y_pred[i] else 'wrong'
for imposter_audio_file in map(
lambda x: 'test-{}.wav'.format(x), range(5)):
fs, signal = wavfile.read(imposter_audio_file)
signal = monotize_signal(signal)
imposter_x = mix_feature((fs, signal))
print gmmset.predict_one_with_rejection(imposter_x)
