def _generate_aldebaran_dataset(files,
nfft=1024,
expected_fs=48000,
window_block=None):
assert (files != [])
res = []
for num, f in enumerate(files):
try:
data = {}
data['file_path'], data['file_name'] = os.path.split(f)
data['full_filename'] = f
data['expected_class'] = data['file_name'].split('-')[0]
signal, fs = load_sound(f)
if fs != expected_fs:
print(
"warning file %s, wrong fs %s, using it.. please remove the file if you don't want"
% (f, fs))
#continue
for frame_feature in extract_mfcc_features_one_channel(
signal, nfft=nfft, window_block=window_block, fs=fs):
data['features'] = frame_feature
res.append(data)
except Exception as e:
print("ERROR on %s" % f)
print(traceback.format_exc())
return res
def _generate_humavips_dataset(glob_file_pattern="/mnt/protolab_server/media/sounds/datasets/NAR_dataset/*/*.wav", nfft=1024):
files = glob.glob(glob_file_pattern)
assert(files!=[])
res = []
for num, f in enumerate(files):
try:
data = {}
data['file_path'], data['file_name'] = os.path.split(f)
data['expected_class'] = os.path.split(data['file_path'])[-1]
signal, fs = load_sound(f)
data['features'] = extract_mfcc_features_one_channel(signal, nfft=nfft)
res.append(data)
except Exception as e:
print("ERROR on %s" % f)
print(traceback.format_exc())
return res
def _generate_humavips_dataset(
glob_file_pattern="/mnt/protolab_server/media/sounds/datasets/NAR_dataset/*/*.wav",
nfft=1024):
files = glob.glob(glob_file_pattern)
assert (files != [])
res = []
for num, f in enumerate(files):
try:
data = {}
data['file_path'], data['file_name'] = os.path.split(f)
data['expected_class'] = os.path.split(data['file_path'])[-1]
signal, fs = load_sound(f)
data['features'] = extract_mfcc_features_one_channel(signal,
nfft=nfft)
res.append(data)
except Exception as e:
print("ERROR on %s" % f)
print(traceback.format_exc())
return res
def _generate_aldebaran_dataset(files, nfft=1024, expected_fs=48000, window_block=None):
assert(files!=[])
res = []
for num, f in enumerate(files):
try:
data = {}
data['file_path'], data['file_name'] = os.path.split(f)
data['full_filename'] = f
data['expected_class'] = data['file_name'].split('-')[0]
signal, fs = load_sound(f)
if fs!=expected_fs:
print("warning file %s, wrong fs %s, using it.. please remove the file if you don't want" % (f, fs))
#continue
for frame_feature in extract_mfcc_features_one_channel(signal, nfft=nfft, window_block=window_block, fs=fs):
data['features'] = frame_feature
res.append(data)
except Exception as e:
print("ERROR on %s" % f)
print(traceback.format_exc())
return res
def _generate_8k_dataset_dict(glob_file_pattern='/mnt/protolab_server_8k/fold*/*.wav', nfft=1024, downsampling_freq=None):
"""
:param glob_file_pattern:
:param nfft:
:param downsampling_freq: if set it's used for downsampling
:return:
"""
files = glob.glob(glob_file_pattern)
assert(files!=[])
res = []
for num, f in enumerate(files):
try:
data = {}
data['file_path'], data['file_name'] = os.path.split(f)
signal, fs = load_sound(f)
# using channel_1 only
if downsampling_freq:
signal, fs = downsample_signal(signal, origin_fs=fs, final_fs=downsampling_freq)
data['fs'] = fs
try:
features = extract_mfcc_features_one_channel(signal, nfft=nfft)
data['features'] = features
except Exception as e:
import IPython
IPython.embed()
res.append(data)
except Exception as e:
print("ERROR on %s" % f)
print(traceback.format_exc())
return res