def compare(control_path, exp_path):
"""
Compares two wav files and returns a score. Uses mel frequency ceptrum coefficients as well as dynamic time warping.
:param control_path: the 'correct' wav - what you are comparing to
:param exp_path: the unknown wav
"""
(rate,sig) = wavread(control_path)
(rate2,sig2) = wavread(exp_path)
x = mfcc(sig,rate)
y = mfcc(sig2,rate2)
dist, cost, acc = dtw.dtw(x, y, dist=lambda x, y: dtw.norm(x - y, ord=1))\
return dist
def compare(control_path, exp_path):
"""
Compares two wav files and returns a score. Uses mel frequency ceptrum coefficients as well as dynamic time warping.
:param control_path: the 'correct' wav - what you are comparing to
:param exp_path: the unknown wav
"""
(rate, sig) = wavread(control_path)
(rate2, sig2) = wavread(exp_path)
x = mfcc(sig, rate)
y = mfcc(sig2, rate2)
dist, cost, acc = dtw.dtw(x, y, dist=lambda x, y: dtw.norm(x - y, ord=1))\
return dist
def compare_mfcc(*args):
if len(args) < 2:
print 'Invalid number of arguments'
return -1
input_paths = args[1:]
processed_wav_data = []
if check_file_paths(input_paths) == -1:
return -1
mfcc_data = []
for path in input_paths:
(rate, sig) = wavread(path)
mfcc_data.append(mfcc(sig, rate))
zipped_data = zip(*mfcc_data)
mean_data = map(np.mean, zipped_data)
user_path = args[0]
(rate, sig) = wavread(user_path)
user_data = mfcc(sig, rate)
dist, cost, acc = dtw.dtw(mean_data,
user_data,
dist=lambda x, y: dtw.norm(x - y, ord=1))
return dist
# # Images for debugging purposes
# cv2.imwrite('nativethresh.png', native_thresh)
# cv2.imwrite('userthresh.png', user_thresh)
# # cv2.imwrite('diffthresh.png', diff_thresh)
# non_zeros = np.count_nonzero(diff_thresh.flatten(0))
# print non_zeros/len(diff_thresh.flatten(0))
# # CLEANUP
# try:
# # os.remove('native.png')
# # os.remove('user.png')
# os.remove('difference.png')
# except OSError:
# pass
(rate, sig) = wav.read(native_wav_path)
mfcc_feat = mfcc(sig, rate)
fbank_feat = logfbank(sig, rate)
(rate2, sig2) = wav.read(user_wav_path)
mfcc_feat2 = mfcc(sig2, rate2)
fbank_feat2 = logfbank(sig2, rate2)
x = mfcc(sig, rate)
y = mfcc(sig2, rate2)
dist, cost, acc = dtw.dtw(x, y, dist=lambda x, y: dtw.norm(x - y, ord=1))
print dist