def test_winlen(file_list, csv_file_name):
if not os.path.isfile(csv_file_name):
print('-------WIN LENGTH TESTING -------')
win_lens = [0.01, 0.025, 0.05, 0.07, 0.1, 0.2, 0.25, 0.3, 0.035, 0.4, 0.45, 0.5, 0.55, 0.6]
output = {}
for winLen in win_lens:
params_dict = get_mfcc_matrices_for_each_speaker(file_list, winlen=winLen, nfft=2048)
confusion_matrix = cross_validation(params_dict)
recogn_ratio = calc_recogn_ratio(confusion_matrix)
output[winLen] = recogn_ratio
write_to_csv(output, csv_file_name)
def test_ncomponents(file_list, csv_file_name):
if not os.path.isfile(csv_file_name):
print('-------NUMBER OF COMPONENTS TESTING-------')
ncomponents_nums = range(1, 20)
output = {}
for ncomponents_num in ncomponents_nums:
print(ncomponents_num, ' components testing ...')
params_dict = get_mfcc_matrices_for_each_speaker(file_list)
confusion_matrix = cross_validation(params_dict, n_components=ncomponents_num)
recogn_ratio = calc_recogn_ratio(confusion_matrix)
output[ncomponents_num] = recogn_ratio
write_to_csv(output, csv_file_name)
print('-------NUMBER OF COMPONENTS TESTING FINISHED----')
def test_nfilt(file_list, csv_file_name):
if not os.path.isfile(csv_file_name):
print('-------NUMBER OF FILTERS TESTING -------')
filter_nums = range(5, 26)
output = {}
for filter_num in filter_nums:
print(filter_num, ' nfilt testing ...')
params_dict = get_mfcc_matrices_for_each_speaker(file_list, nfilt=filter_num)
confusion_matrix = cross_validation(params_dict)
recogn_ratio = calc_recogn_ratio(confusion_matrix)
output[filter_num] = recogn_ratio
write_to_csv(output, csv_file_name)
print('-------NUMBER OF FILTERS TESTING FINISHED----')
def test_nfft(file_list, csv_file_name):
if not os.path.isfile(csv_file_name):
print('-------NUMBER OF NFFT TESTING-------')
nfft_nums = [64, 128, 256, 512, 1024, 2048, 4096]
output = {}
for nfft_num in nfft_nums:
print(nfft_num, ' nfft testing ...')
params_dict = get_mfcc_matrices_for_each_speaker(file_list, nfft=nfft_num)
confusion_matrix = cross_validation(params_dict)
recogn_ratio = calc_recogn_ratio(confusion_matrix)
output[nfft_num] = recogn_ratio
write_to_csv(output, csv_file_name)
print('-------NFFT TESTING FINISHED----')
def test_numcep(file_list, csv_file_name):
if not os.path.isfile(csv_file_name):
print('-------NUMBER OF CEPSTRUMS TESTING -------')
cep_nums = range(4,14)
output = {}
for cep_num in cep_nums:
print(cep_num, ' cepstrums testing ...')
params_dict = get_mfcc_matrices_for_each_speaker(file_list, numcep=cep_num,)
confusion_matrix = cross_validation(params_dict)
recogn_ratio = calc_recogn_ratio(confusion_matrix)
output[cep_num] = recogn_ratio
write_to_csv(output, csv_file_name)
print('-------NUMBER OF CEPSTRUMS TESTING FINISHED----')