def getDist(args):
sample = args['s_path']
word = args['w_path']
model = args['model']
trans = args['trans']
sample_wav, fs = walkman.load(sample)
sample_feat = logfbank(sample_wav,
samplerate=fs,
lowfreq=64,
highfreq=8000,
nfilt=40,
nfft=2048)
sample_feat_trans = featureTransform(sample_feat, trans)
word_wav, fs = walkman.load(word)
word_feat = logfbank(word_wav,
samplerate=fs,
lowfreq=64,
highfreq=8000,
nfilt=40,
nfft=2048)
word_feat_trans = featureTransform(word_feat, trans)
y_sample = model.predict(sample_feat_trans)
y_word = model.predict(word_feat_trans)
dist, _, _, _ = dtw(makeList(y_word), makeList(y_sample), euclidean)
args['dist'] = dist
return args
def makeFeature(args):
sample = args['path']
trans = args['trans']
sample_wav, fs = walkman.load(sample)
sample_feat = logfbank(sample_wav, samplerate=fs, lowfreq=64, highfreq=8000, nfilt=40, nfft=2048)
sample_feat_trans = featureTransform(sample_feat, trans)
args['feat'] = sample_feat_trans
return args
def playFile(truth, sample, model, trans, nnet_dict):
t = list()
# Starting trial
t.append(time.time())
imChange('blank')
data, fs = walkman.load(truth['path'])
print('Starting trial {0:s}...'.format(truth['path']))
while time.time() - t[0] < 1.5:
None
# File will play after 1.5 seconds
t.append(time.time())
imChange('listen')
while time.time() - t[0] < 2:
None
# Playing file
print('Playing')
walkman.play(data, fs)
while time.time() - t[0] < 3.5:
None
# Rest time begins
t.append(time.time())
print('Rest')
imChange('rest')
while time.time() - t[0] < 5:
None
# Speak time
print('Speak')
imChange('speak')
t.append(time.time())
rec, fs = walkman.record_nowait(2.5, 16000, 1)
while (time.time() - t[3] < 2.5):
None
# Recording ends here. Scoring can now begin
t.append(time.time())
imChange('triangle')
print('Saving')
walkman.save(sample['path'], rec, 16000)
# Doing VAD
first = time.time()
# sample['path'] = 'recordings/data2.wav'
vad.makeVad(sample['path'], 'temp.wav')
sample['path'] = 'temp.wav'
# Scoring
print('Scoring')
sc = score(sample, truth, model, trans, nnet_dict)
print(sc)
print('Scored in {0:.2f} seconds\n'.format(time.time() - first))
imChange('blank')
return t
def score(sample, truth, model, trans):
sample_wav, fs = walkman.load(sample)
sample_feat = logfbank(sample_wav, samplerate=fs, lowfreq=64, highfreq=8000, nfilt=40)
sample_feat_trans = featureTransform(sample_feat, trans)
print(np.shape(sample_feat_trans))
x = sample_feat_trans
y_sample = model.predict(x, batch_size=512)
y_truth = load_truth(truth)
dist, _, _, _ = dtw(makeList(y_truth), makeList(y_sample), klDist)
return dist
def phase2b(truth, sample): #, model, trans, nnet_dict):
dict = config.getPhase2b()
t = list()
# Starting trial
t.append(time.time())
imChange('blank')
data, fs = walkman.load(truth['endpath'])
print('Starting trial {0:s}...'.format(truth['path']))
while time.time() - t[0] < dict['rest1']:
None
t.append(time.time())
imChange(truth['image'], path=truth['impath'])
print('Image')
while time.time() - t[0] < dict['rest1'] + dict['image']:
None
imChange('blank')
time.sleep(dict['rest2'])
# Speak time
print('Speak')
imChange('speak')
t.append(time.time())
rec, fs = walkman.record_nowait(2.5, 16000, 1)
while (time.time() - t[2] < dict['record']):
None
# Recording ends here. Scoring can now begin
t.append(time.time())
imChange('triangle')
print('Saving')
walkman.save(sample['path'], rec, 16000)
# Playing file
imChange('listen')
print('Playing')
walkman.play(data, fs)
while time.time() - t[3] < dict['listen']:
None
# # Doing VAD
# first = time.time()
# # sample['path'] = 'recordings/data2.wav'
# vad.makeVad(sample['path'], 'temp.wav')
# sample['path'] = 'temp.wav'
# # Scoring
# print('Scoring')
# sc = score(sample, truth, model, trans, nnet_dict)
# print(sc)
# print('Scored in {0:.2f} seconds\n'.format(time.time() - first))
# # Show score image
# imScore(sc)
# time.sleep(dict['score'])
return t
def playFile(truth, subject, sender=None):
dictn = {'rest1': 0.5, 'delay': 1.5, 'listen': 1.5}
t = list()
t.append(time.time())
# Load file
data, fs = walkman.load(truth['path'])
print('Starting trial {0:s}...'.format(truth['path']))
# Playing file
t.append(time.time()) # append time when starts playing
print('Playing')
walkman.play(data, fs)
# Keypress time
t.append(time.time()) # append time when stops playing
imChange('keypress')
print('Keypress...')
keypress = 3 # getch()
t.append(time.time()) # append time when key is pressed
while keypress > 2:
keypress = ord(getch()) - ord(str(1)) + 1
print(keypress)
# while int(float(keypress)) > 2:
# keypress = getch()
# print(int(float(keypress)))
with open('recordings/{0:s}/keys.csv'.format(subject), 'a+') as file:
file.write(
'{0:d},{1:s},{2:d},{3:s},{4:s},{5:5.2f},{6:5.3f},{7:5.3f}\n'.
format(truth['prompt'], truth['path'], truth['npkr'],
str(keypress), truth['trial'], t[1] - t[0], t[2] - t[0],
t[3] - t[0]))
if keypress == truth['npkr']:
imChange('correct')
score = 1
else:
imChange('wrong')
score = 0
time.sleep(1)
imChange('blank') # trial ends
return score
def phase2a(truth, sample):
dict = config.getPhase2a()
t = list()
# Starting trial
t.append(time.time())
imChange('blank')
data, fs = walkman.load(truth['endpath'])
print('Starting trial {0:s}...'.format(truth['path']))
while time.time() - t[0] < dict['rest1']:
None
t.append(time.time())
imChange(truth['image'], path=truth['impath'])
print('Image')
while time.time() - t[0] < dict['rest1'] + dict['image']:
None
imChange('listen')
time.sleep(dict['delay'])
# Playing file
print('Playing')
walkman.play(data, fs)
while time.time() - t[0] < dict['rest1'] + dict['image'] + dict['listen']:
None
# Rest time begins
t.append(time.time())
print('Rest')
imChange('rest')
while time.time(
) - t[0] < dict['rest1'] + dict['image'] + dict['listen'] + dict['rest2']:
None
# Speak time
print('Speak')
imChange('speak')
t.append(time.time())
rec, fs = walkman.record_nowait(2.5, 16000, 1)
while (time.time() - t[3] < dict['record']):
None
# Recording ends here. Scoring can now begin
t.append(time.time())
imChange('triangle')
print('Saving')
walkman.save(sample['path'], rec, 16000)
imChange('blank')
return t
