def generate_lf0(source_f0_folder, target_lf0_folder, file_lengths):
io_funcs = BinaryIOCollection()
for file_id, file_length in file_lengths.iteritems():
source_file_path = os.path.join(source_f0_folder,
'{}.f0'.format(file_id))
target_file_path = os.path.join(target_lf0_folder,
'{}.lf0'.format(file_id))
with open(source_file_path, 'rt') as handle:
lines = handle.readlines()
f0s = [float(line) for line in lines]
if len(lines) <= file_length:
f0s += [0.] * (file_length - len(lines))
else:
f0s = f0s[:file_length]
lf0s = [-1e+10] * file_length
for i in xrange(file_length):
if f0s[i] <= 10.0:
continue
lf0s[i] = math.log(f0s[i])
print(target_file_path)
io_funcs.array_to_binary_file(lf0s, target_file_path)
print
def load_covariance(self, var_file_dict, out_dimension_dict):
io_funcs = BinaryIOCollection()
for feature_name in list(var_file_dict.keys()):
var_values, dimension = io_funcs.load_binary_file_frame(var_file_dict[feature_name], 1)
var_values = numpy.reshape(var_values, (out_dimension_dict[feature_name], 1))
self.var[feature_name] = var_values
def shift_for_one_utterance(self, utt, feat_dim, semi):
if semi == 0:
return os.path.basename(utt)
io_funcs = BinaryIOCollection()
feat, num_frame = io_funcs.load_binary_file_frame(utt, feat_dim)
for f in feat:
self.shift_pitch_feat(f[curr_start_ind: curr_end_ind + 1], semi)
self.shift_pitch_feat(f[prev_start_ind: prev_end_ind + 1], semi)
self.shift_pitch_feat(f[next_start_ind: next_end_ind + 1], semi)
if semi > 0:
filename = utt + '_u' + str(semi)
else:
filename = utt + '_d' + str(-semi)
io_funcs.array_to_binary_file(feat, filename)
return os.path.basename(filename)
class AlignFeats(object):
def __init__(self):
self.io_funcs = BinaryIOCollection()
def align_src_feats(self, src_feat_file, src_aligned_feat_file, feat_dim, dtw_path_dict):
'''
align source feats as per the dtw path (matching target length)
'''
src_features, frame_number = self.io_funcs.load_binary_file_frame(src_feat_file, feat_dim)
tgt_length = len(dtw_path_dict)
src_aligned_features = numpy.zeros((tgt_length, feat_dim))
for i in range(tgt_length):
src_aligned_features[i, ] = src_features[dtw_path_dict[i]]
self.io_funcs.array_to_binary_file(src_aligned_features, src_aligned_feat_file)
def duration_decomposition(self, in_file_list, dimension,
out_dimension_dict, file_extension_dict):
logger = logging.getLogger('param_generation')
logger.debug('duration_decomposition for %d files' % len(in_file_list))
state_number = 5 ## hard coding, try removing in future?
if len(list(out_dimension_dict.keys())) > 1:
logger.critical(
"we don't support any additional features along with duration as of now."
)
sys.exit(1)
else:
feature_name = list(out_dimension_dict.keys())[0]
io_funcs = BinaryIOCollection()
findex = 0
flen = len(in_file_list)
for file_name in in_file_list:
findex = findex + 1
dir_name = os.path.dirname(file_name)
file_id = os.path.splitext(os.path.basename(file_name))[0]
features, frame_number = io_funcs.load_binary_file_frame(
file_name, dimension)
gen_features = numpy.int32(numpy.round(features))
gen_features[gen_features < 1] = 1
if dimension > state_number:
gen_features = gen_features[:, state_number]
logger.info('processing %4d of %4d: %s' %
(findex, flen, file_name))
new_file_name = os.path.join(
dir_name, file_id + file_extension_dict[feature_name])
io_funcs.array_to_binary_file(gen_features, new_file_name)
logger.debug('wrote to file %s' % new_file_name)
class AlignFeats(object):
def __init__(self):
self.io_funcs = BinaryIOCollection()
def align_src_feats(self, src_feat_file, src_aligned_feat_file, feat_dim,
dtw_path_dict):
'''
align source feats as per the dtw path (matching target length)
'''
src_features, frame_number = self.io_funcs.load_binary_file_frame(
src_feat_file, feat_dim)
tgt_length = len(dtw_path_dict)
src_aligned_features = numpy.zeros((tgt_length, feat_dim))
for i in range(tgt_length):
src_aligned_features[i, ] = src_features[dtw_path_dict[i]]
self.io_funcs.array_to_binary_file(src_aligned_features,
src_aligned_feat_file)
def make_equal_frames(self, in_file_list, ref_file_list, in_dimension_dict):
logger = logging.getLogger("test")
logger.info('making equal number of lines...')
io_funcs = BinaryIOCollection()
utt_number = len(in_file_list)
for i in xrange(utt_number):
in_file_name = in_file_list[i]
in_data_stream_name = in_file_name.split('.')[-1]
in_feature_dim = in_dimension_dict[in_data_stream_name]
in_features, in_frame_number = io_funcs.load_binary_file_frame(in_file_name, in_feature_dim)
ref_file_name = ref_file_list[i]
ref_data_stream_name = ref_file_name.split('.')[-1]
ref_feature_dim = in_dimension_dict[ref_data_stream_name]
ref_features, ref_frame_number = io_funcs.load_binary_file_frame(ref_file_name, ref_feature_dim)
target_features = numpy.zeros((ref_frame_number, in_feature_dim))
if in_frame_number == ref_frame_number:
continue;
elif in_frame_number > ref_frame_number:
target_features[0:ref_frame_number, ] = in_features[0:ref_frame_number, ]
elif in_frame_number < ref_frame_number:
target_features[0:in_frame_number, ] = in_features[0:in_frame_number, ]
io_funcs.array_to_binary_file(target_features, in_file_name)
logger.info('Finished: made equal rows in data stream %s with reference to data stream %s ' %(in_data_stream_name, ref_data_stream_name))
def prepare_data(self, in_file_list_dict, out_file_list, in_dimension_dict,
out_dimension_dict):
logger = logging.getLogger("acoustic_comp")
stream_start_index = {}
stream_dim_index = 0
for stream_name in out_dimension_dict.keys():
if not stream_start_index.has_key(stream_name):
stream_start_index[stream_name] = stream_dim_index
stream_dim_index += out_dimension_dict[stream_name]
io_funcs = BinaryIOCollection()
for i in xrange(self.file_number):
out_file_name = out_file_list[i]
#if os.path.isfile(out_file_name):
# logger.info('processing file %4d of %4d : %s exists' % (i+1, self.file_number, out_file_name))
# continue
logger.info('processing file %4d of %4d : %s' %
(i + 1, self.file_number, out_file_name))
out_data_matrix = None
out_frame_number = 0
for k in xrange(self.data_stream_number):
data_stream_name = self.data_stream_list[k]
in_file_name = in_file_list_dict[data_stream_name][i]
in_feature_dim = in_dimension_dict[data_stream_name]
features, frame_number = io_funcs.load_binary_file_frame(
in_file_name, in_feature_dim)
if k == 0:
out_frame_number = frame_number
out_data_matrix = numpy.zeros(
(out_frame_number, self.out_dimension))
if frame_number > out_frame_number:
features = features[0:out_frame_number, ]
frame_number = out_frame_number
try:
assert out_frame_number == frame_number
except AssertionError:
logger.critical(
'the frame number of data stream %s is not consistent with others: current %d others %d'
% (data_stream_name, out_frame_number, frame_number))
raise
dim_index = stream_start_index[data_stream_name]
if data_stream_name in ['lf0', 'F0']: ## F0 added for GlottHMM
features, vuv_vector = self.interpolate_f0(features)
### if vuv information to be recorded, store it in corresponding column
if self.record_vuv:
out_data_matrix[0:out_frame_number,
stream_start_index['vuv']:
stream_start_index['vuv'] +
1] = vuv_vector
out_data_matrix[0:out_frame_number, dim_index:dim_index +
in_feature_dim] = features
dim_index = dim_index + in_feature_dim
if self.compute_dynamic[data_stream_name]:
delta_features = self.compute_dynamic_matrix(
features, self.delta_win, frame_number, in_feature_dim)
acc_features = self.compute_dynamic_matrix(
features, self.acc_win, frame_number, in_feature_dim)
out_data_matrix[0:out_frame_number, dim_index:dim_index +
in_feature_dim] = delta_features
dim_index = dim_index + in_feature_dim
out_data_matrix[0:out_frame_number, dim_index:dim_index +
in_feature_dim] = acc_features
### write data to file
io_funcs.array_to_binary_file(out_data_matrix, out_file_name)
logger.debug(' wrote %d frames of features', out_frame_number)
'vuv' : '.vuv'}
var_file_dict = {'mgc':'{}/mgc.var'.format(args.var_dir),
'vuv':'{}/vuv.var'.format(args.var_dir),
'lf0':'{}/lf0.var'.format(args.var_dir)}
generator = ParameterGeneration()
# out_dimension_dict is the cmp structrue of your nnet output cmp
generator.acoustic_decomposition(in_file_list, 127, out_dimension_dict, file_extension_dict, var_file_dict)
if not os.path.exists(lf0_dir):
os.mkdir(lf0_dir)
if not os.path.exists(mgc_dir):
os.mkdir(mgc_dir)
os.system('mv {}/*.lf0 {}'.format(cmp_dir, lf0_dir))
os.system('mv {}/*.mgc {}'.format(cmp_dir, mgc_dir))
io_funcs = BinaryIOCollection()
inf_float = -1.0e+10
for item in os.listdir(cmp_dir):
vuv = numpy.reshape(numpy.fromfile(os.path.join(cmp_dir, item), dtype=numpy.float32), [-1,127])[:,123]
name, ext = os.path.splitext(item)
lf0 = numpy.reshape(numpy.fromfile(os.path.join(lf0_dir, "{}.lf0".format(name)),dtype=numpy.float32),[-1,1])
mgc = numpy.reshape(numpy.fromfile(os.path.join(mgc_dir, "{}.mgc".format(name)),dtype=numpy.float32),[-1,41])
mgc = signal.convolve2d(
mgc, [[1.0 / 3], [1.0 / 3], [1.0 / 3]], mode="same", boundary="symm")
lf0[vuv < 0.5] = inf_float
io_funcs.array_to_binary_file(lf0, os.path.join(lf0_dir, "{}.lf0".format(name)))
io_funcs.array_to_binary_file(mgc, os.path.join(mgc_dir, "{}.mgc".format(name)))
def acoustic_decomposition(self, in_file_list, dimension, out_dimension_dict, file_extension_dict, var_file_dict, do_MLPG=True, cfg=None):
print ('param_generation')
print ('acoustic_decomposition for %d files' % len(in_file_list) )
self.load_covariance(var_file_dict, out_dimension_dict)
stream_start_index = {}
dimension_index = 0
recorded_vuv = True
vuv_dimension = None
for feature_name in list(out_dimension_dict.keys()):
if feature_name != 'vuv':
stream_start_index[feature_name] = dimension_index
else:
vuv_dimension = dimension_index
dimension_index += out_dimension_dict[feature_name]
io_funcs = BinaryIOCollection()
mlpg_algo = MLParameterGeneration()
findex=0
flen=len(in_file_list)
for file_name in in_file_list:
findex=findex+1
dir_name = os.path.dirname(file_name)
file_id = os.path.splitext(os.path.basename(file_name))[0]
features, frame_number = io_funcs.load_binary_file_frame(file_name, dimension)
print('processing %4d of %4d: %s' % (findex,flen,file_name) )
for feature_name in self.gen_wav_features:
print(' feature: %s' % feature_name)
current_features = features[:, stream_start_index[feature_name]:stream_start_index[feature_name]+out_dimension_dict[feature_name]]
if FAST_MLPG:
### fast version wants variance per frame, not single global one:
var = self.var[feature_name]
var = numpy.transpose(numpy.tile(var,frame_number))
else:
var = self.var[feature_name]
# print var.shape[1]
if do_MLPG == False:
gen_features = current_features
else:
gen_features = mlpg_algo.generation(current_features, var, out_dimension_dict[feature_name]//3)
print(' feature dimensions: %d by %d' %(gen_features.shape[0], gen_features.shape[1]))
if feature_name in ['lf0', 'F0']:
if 'vuv' in stream_start_index:
vuv_feature = features[:, stream_start_index['vuv']:stream_start_index['vuv']+1]
for i in range(frame_number):
if new_vuv_feature[i] < 0.5:
gen_features[i, 0] = self.inf_float
new_file_name = os.path.join(dir_name, file_id + file_extension_dict[feature_name])
if self.enforce_silence:
silence_pattern = cfg.silence_pattern
label_align_dir = cfg.in_label_align_dir
in_f = open(label_align_dir+'/'+file_id+'.lab','r')
for line in in_f.readlines():
line = line.strip()
if len(line) < 1:
continue
temp_list = re.split('\s+', line)
start_time = int(int(temp_list[0])*(10**-4)/5)
end_time = int(int(temp_list[1])*(10**-4)/5)
full_label = temp_list[2]
label_binary_flag = self.check_silence_pattern(full_label, silence_pattern)
if label_binary_flag:
if feature_name in ['lf0', 'F0', 'mag']:
gen_features[start_time:end_time, :] = self.inf_float
else:
gen_features[start_time:end_time, :] = 0.0
io_funcs.array_to_binary_file(gen_features, new_file_name)
print(' wrote to file %s' % new_file_name)
def compute_distortion(self, file_id_list, reference_dir, generation_dir,
file_ext, feature_dim):
total_voiced_frame_number = 0
distortion = 0.0
vuv_error = 0
total_frame_number = 0
io_funcs = BinaryIOCollection()
ref_all_files_data = numpy.reshape(numpy.array([]), (-1, 1))
gen_all_files_data = numpy.reshape(numpy.array([]), (-1, 1))
for file_id in file_id_list:
ref_file_name = reference_dir + '/' + file_id.strip() + file_ext
gen_file_name = generation_dir + '/' + file_id.strip() + file_ext
ref_data, ref_frame_number = io_funcs.load_binary_file_frame(
ref_file_name, feature_dim)
gen_data, gen_frame_number = io_funcs.load_binary_file_frame(
gen_file_name, feature_dim)
if ref_frame_number != gen_frame_number:
self.logger.critical(
"The number of frames is not the same: %d vs %d. Error in compute_distortion.py\n."
% (ref_frame_number, gen_frame_number))
raise
if file_ext == '.lf0':
ref_all_files_data = numpy.concatenate(
(ref_all_files_data, ref_data), axis=0)
gen_all_files_data = numpy.concatenate(
(gen_all_files_data, gen_data), axis=0)
temp_distortion, temp_vuv_error, voiced_frame_number = self.compute_f0_mse(
ref_data, gen_data)
vuv_error += temp_vuv_error
total_voiced_frame_number += voiced_frame_number
elif file_ext == '.dur':
ref_data = numpy.reshape(numpy.sum(ref_data, axis=1), (-1, 1))
gen_data = numpy.reshape(numpy.sum(gen_data, axis=1), (-1, 1))
ref_all_files_data = numpy.concatenate(
(ref_all_files_data, ref_data), axis=0)
gen_all_files_data = numpy.concatenate(
(gen_all_files_data, gen_data), axis=0)
continue
elif file_ext == '.mgc':
temp_distortion = self.compute_mse(ref_data[:, 1:feature_dim],
gen_data[:, 1:feature_dim])
else:
temp_distortion = self.compute_mse(ref_data, gen_data)
distortion += temp_distortion
total_frame_number += ref_frame_number
if file_ext == '.dur':
dur_rmse = self.compute_rmse(ref_all_files_data,
gen_all_files_data)
dur_corr = self.compute_corr(ref_all_files_data,
gen_all_files_data)
return dur_rmse, dur_corr
elif file_ext == '.lf0':
distortion /= float(total_voiced_frame_number)
vuv_error /= float(total_frame_number)
distortion = numpy.sqrt(distortion)
f0_corr = self.compute_f0_corr(ref_all_files_data,
gen_all_files_data)
return distortion, f0_corr, vuv_error
else:
distortion /= float(total_frame_number)
return distortion
def __init__(self):
self.io_funcs = BinaryIOCollection()
return phone, st_arr, ph_arr, mean_f0_arr
def zeros(self, m, n):
if(n == 1):
arr = np.ndarray((m,), float)
else:
arr = np.ndarray((m, n), float)
arr.fill(0)
return arr
if __name__ == "__main__":
dnn_dir = '/afs/inf.ed.ac.uk/group/cstr/projects/phd/s1432486/work/dnn_tts_blzpilot/'
label_align_dir = os.path.join(dnn_dir, 'two_stage_mtldnn/data/label_state_align')
htsclass = readHTSlabelFile()
io_funcs = BinaryIOCollection()
DFP = 1
if DFP:
parseLabFile = True;
if parseLabFile:
filelist = os.path.join(dnn_dir, 'two_stage_mtldnn/data/file_id_list.scp')
list_of_files = io_funcs.load_file_list(filelist)
max_syl_dur = 0
max_syl_dur_filename = ''
for i in range(len(list_of_files)):
filename = list_of_files[i]
print filename
def load_next_partition(self):
print 'Loading Next Partition'
sftp = pysftp.Connection('eddie.ecdf.ed.ac.uk',username='******',password='******')
i_temp_set = numpy.empty((self.buffer_size, self.n_ins))
o_temp_set = numpy.empty((self.buffer_size, self.n_outs))
current_index = 0
### first check whether there are remaining data from previous utterance
if self.remain_frame_number > 0:
remain_frames = self.remain_frame_number - current_index
remain_size = self.i_remain_data.shape[0]
if remain_frames != remain_size:
if remain_frames < remain_size:
if remain_size - remain_frames <= 20:
print "Check remain_size"
else:
print "We delete", self.remain_frame_number,"frames"
self.remain_frame_number = 0
elif remain_frames > remain_size:
self.remain_frame_number = self.remain_frame_number - (remain_frames - remain_size)
i_temp_set[current_index:self.remain_frame_number, ] = self.i_remain_data
o_temp_set[current_index:self.remain_frame_number, ] = self.o_remain_data
current_index += self.remain_frame_number
self.remain_frame_number = 0
io_function = BinaryIOCollection()
while True:
if current_index >= self.buffer_size:
break
if self.file_index >= self.list_size:
self.end_reading = True
self.file_index = 0
break
sftp.get(self.i_list[self.file_index])
sftp.get(self.o_list[self.file_index])
i_file_name = self.extract_file_id(self.i_list[self.file_index])
o_file_name = self.extract_file_id(self.o_list[self.file_index])
remove_items = []
while (os.path.isfile(i_file_name) and os.path.isfile(o_file_name)) is False:
print i_file_name," is :", os.path.isfile(i_file_name), "in beginning of load_next_partition"
print o_file_name," is :", os.path.isfile(o_file_name), "in beginning of load_next_partition"
remove_items.append(i_file_name)
remove_items.append(o_file_name)
self.file_index +=1
sftp.get(self.i_list[self.file_index])
sftp.get(self.o_list[self.file_index])
i_file_name = self.extract_file_id(self.i_list[self.file_index])
o_file_name = self.extract_file_id(self.o_list[self.file_index])
remove_items.append(i_file_name)
remove_items.append(o_file_name)
i_features, lab_frame_number = io_function.load_binary_file_frame(i_file_name , self.n_ins)
o_features, out_frame_number = io_function.load_binary_file_frame(o_file_name, self.n_outs)
for item in remove_items:
if os.path.isfile(item) is True:
os.remove(item)
remove_items = []
frame_number = lab_frame_number
if abs(lab_frame_number - out_frame_number) < 5: ## we allow small difference here. may not be correct, but sometimes, there is one/two frames difference
if lab_frame_number > out_frame_number:
frame_number = out_frame_number
else:
while abs(lab_frame_number - out_frame_number) > 5:
self.file_index += 1
#############
while (os.path.isfile(i_file_name) and os.path.isfile(o_file_name)) is False:
print i_file_name," is :", os.path.isfile(i_file_name), "in ELSE of load_next_partition"
print o_file_name," is :", os.path.isfile(o_file_name), "in ELSE of load_next_partition"
remove_items.append(i_file_name)
remove_items.append(o_file_name)
sftp.get(self.i_list[self.file_index])
sftp.get(self.o_list[self.file_index])
i_file_name = self.extract_file_id(self.i_list[self.file_index])
o_file_name = self.extract_file_id(self.o_list[self.file_index])
remove_items.append(i_file_name)
remove_items.append(o_file_name)
i_features, lab_frame_number = io_function.load_binary_file_frame(i_file_name , self.n_ins)
o_features, out_frame_number = io_function.load_binary_file_frame(o_file_name, self.n_outs)
for item in remove_items:
if os.path.isfile(item) is True:
os.remove(item)
remove_items = []
#############
o_features = o_features[0:frame_number, ]
i_features = i_features[0:frame_number, ]
if current_index + frame_number <= self.buffer_size:
i_temp_set[current_index:current_index+frame_number, ] = i_features
o_temp_set[current_index:current_index+frame_number, ] = o_features
current_index = current_index + frame_number
else: ## if current utterance cannot be stored in the block, then leave the remaining part for the next block
used_frame_number = self.buffer_size - current_index
i_temp_set[current_index:self.buffer_size, ] = i_features[0:used_frame_number, ]
o_temp_set[current_index:self.buffer_size, ] = o_features[0:used_frame_number, ]
current_index = self.buffer_size
self.i_remain_data = i_features[used_frame_number:frame_number, ]
self.o_remain_data = o_features[used_frame_number:frame_number, ]
self.remain_frame_number = frame_number - used_frame_number
self.file_index += 1
sftp.close()
i_temp_set = i_temp_set[0:current_index, ]
o_temp_set = o_temp_set[0:current_index, ]
numpy.random.seed(271639)
numpy.random.shuffle(i_temp_set)
numpy.random.seed(271639)
numpy.random.shuffle(o_temp_set)
i_shared_set = self.make_shared(i_temp_set, 'x')
o_shared_set = self.make_shared(o_temp_set, 'y')
io_shared_set = (i_shared_set, o_shared_set)
return io_shared_set, i_temp_set, o_temp_set
def load_next_utterance(self):
print("Loading Next Utterance")
i_temp_set = numpy.empty((self.buffer_size, self.n_ins))
o_temp_set = numpy.empty((self.buffer_size, self.n_outs))
io_function = BinaryIOCollection()
sftp = pysftp.Connection('eddie.ecdf.ed.ac.uk',
username='******',
password='******')
sftp.get(self.i_list[self.file_index])
sftp.get(self.o_list[self.file_index])
i_file_name = self.extract_file_id(self.i_list[self.file_index])
o_file_name = self.extract_file_id(self.o_list[self.file_index])
remove_items = []
while (os.path.isfile(i_file_name)
and os.path.isfile(o_file_name)) is False:
print i_file_name, " is :", os.path.isfile(
i_file_name), "in load_next_utterance"
print o_file_name, " is :", os.path.isfile(
o_file_name), "in load_next_utterance"
remove_items.append(i_file_name)
remove_items.append(o_file_name)
self.file_index += 1
sftp.get(self.i_list[self.file_index])
sftp.get(self.o_list[self.file_index])
i_file_name = self.extract_file_id(self.i_list[self.file_index])
o_file_name = self.extract_file_id(self.o_list[self.file_index])
remove_items.append(i_file_name)
remove_items.append(o_file_name)
sftp.close()
i_features, lab_frame_number = io_function.load_binary_file_frame(
i_file_name, self.n_ins)
o_features, out_frame_number = io_function.load_binary_file_frame(
o_file_name, self.n_outs)
for item in remove_items:
if os.path.isfile(item) is True:
os.remove(item)
remove_items = []
frame_number = lab_frame_number
if abs(
lab_frame_number - out_frame_number
) < 5: ## we allow small difference here. may not be correct, but sometimes, there is one/two frames difference
if lab_frame_number > out_frame_number:
frame_number = out_frame_number
else:
print "The number of frames in label and acoustic features are different : ", lab_frame_number, " vs ", out_frame_number
raise
i_temp_set = o_features[0:frame_number, ]
o_temp_set = i_features[0:frame_number, ]
self.file_index += 1
if self.file_index >= self.list_size:
self.end_reading = True
self.file_index = 0
i_shared_set = self.make_shared(i_temp_set, 'x')
o_shared_set = self.make_shared(o_temp_set, 'y')
io_shared_set = (i_shared_set, o_shared_set)
return io_shared_set, i_temp_set, o_temp_set
import time
import soundfile as sf
import libutils as lu
from scipy import signal
from scipy import interpolate
# Debug:
#from libdevhelpers import *
# tools location: # Hard coded for nom. TODO: Change
_sptk_bin_dir = os.environ[
'HOME'] + '/Dropbox/Projects/sublimetext_as_python_ide/common/SPTK-3.7'
_reaper_bin = os.environ[
'HOME'] + '/Dropbox/Projects/sublimetext_as_python_ide/common/REAPER/build/reaper'
_io = BinaryIOCollection()
_curr_dir = os.path.dirname(os.path.realpath(__file__))
MAGIC = -1.0E+10 # logarithm floor (the same as SPTK)
#------------------------------------------------------------------------------
def shift_to_pm(v_shift):
v_pm = np.cumsum(v_shift)
return v_pm
#------------------------------------------------------------------------------
def pm_to_shift(v_pm):
v_shift = np.diff(np.hstack((0, v_pm)))
return v_shift
def load_next_partition(self):
print 'Loading Next Partition'
sftp = pysftp.Connection('eddie.ecdf.ed.ac.uk',
username='******',
password='******')
i_temp_set = numpy.empty((self.buffer_size, self.n_ins))
o_temp_set = numpy.empty((self.buffer_size, self.n_outs))
current_index = 0
### first check whether there are remaining data from previous utterance
if self.remain_frame_number > 0:
remain_frames = self.remain_frame_number - current_index
remain_size = self.i_remain_data.shape[0]
if remain_frames != remain_size:
if remain_frames < remain_size:
if remain_size - remain_frames <= 20:
print "Check remain_size"
else:
print "We delete", self.remain_frame_number, "frames"
self.remain_frame_number = 0
elif remain_frames > remain_size:
self.remain_frame_number = self.remain_frame_number - (
remain_frames - remain_size)
i_temp_set[
current_index:self.remain_frame_number, ] = self.i_remain_data
o_temp_set[
current_index:self.remain_frame_number, ] = self.o_remain_data
current_index += self.remain_frame_number
self.remain_frame_number = 0
io_function = BinaryIOCollection()
while True:
if current_index >= self.buffer_size:
break
if self.file_index >= self.list_size:
self.end_reading = True
self.file_index = 0
break
sftp.get(self.i_list[self.file_index])
sftp.get(self.o_list[self.file_index])
i_file_name = self.extract_file_id(self.i_list[self.file_index])
o_file_name = self.extract_file_id(self.o_list[self.file_index])
remove_items = []
while (os.path.isfile(i_file_name)
and os.path.isfile(o_file_name)) is False:
print i_file_name, " is :", os.path.isfile(
i_file_name), "in beginning of load_next_partition"
print o_file_name, " is :", os.path.isfile(
o_file_name), "in beginning of load_next_partition"
remove_items.append(i_file_name)
remove_items.append(o_file_name)
self.file_index += 1
sftp.get(self.i_list[self.file_index])
sftp.get(self.o_list[self.file_index])
i_file_name = self.extract_file_id(
self.i_list[self.file_index])
o_file_name = self.extract_file_id(
self.o_list[self.file_index])
remove_items.append(i_file_name)
remove_items.append(o_file_name)
i_features, lab_frame_number = io_function.load_binary_file_frame(
i_file_name, self.n_ins)
o_features, out_frame_number = io_function.load_binary_file_frame(
o_file_name, self.n_outs)
for item in remove_items:
if os.path.isfile(item) is True:
os.remove(item)
remove_items = []
frame_number = lab_frame_number
if abs(
lab_frame_number - out_frame_number
) < 5: ## we allow small difference here. may not be correct, but sometimes, there is one/two frames difference
if lab_frame_number > out_frame_number:
frame_number = out_frame_number
else:
while abs(lab_frame_number - out_frame_number) > 5:
self.file_index += 1
#############
while (os.path.isfile(i_file_name)
and os.path.isfile(o_file_name)) is False:
print i_file_name, " is :", os.path.isfile(
i_file_name), "in ELSE of load_next_partition"
print o_file_name, " is :", os.path.isfile(
o_file_name), "in ELSE of load_next_partition"
remove_items.append(i_file_name)
remove_items.append(o_file_name)
sftp.get(self.i_list[self.file_index])
sftp.get(self.o_list[self.file_index])
i_file_name = self.extract_file_id(
self.i_list[self.file_index])
o_file_name = self.extract_file_id(
self.o_list[self.file_index])
remove_items.append(i_file_name)
remove_items.append(o_file_name)
i_features, lab_frame_number = io_function.load_binary_file_frame(
i_file_name, self.n_ins)
o_features, out_frame_number = io_function.load_binary_file_frame(
o_file_name, self.n_outs)
for item in remove_items:
if os.path.isfile(item) is True:
os.remove(item)
remove_items = []
#############
o_features = o_features[0:frame_number, ]
i_features = i_features[0:frame_number, ]
if current_index + frame_number <= self.buffer_size:
i_temp_set[current_index:current_index +
frame_number, ] = i_features
o_temp_set[current_index:current_index +
frame_number, ] = o_features
current_index = current_index + frame_number
else: ## if current utterance cannot be stored in the block, then leave the remaining part for the next block
used_frame_number = self.buffer_size - current_index
i_temp_set[current_index:self.buffer_size, ] = i_features[
0:used_frame_number, ]
o_temp_set[current_index:self.buffer_size, ] = o_features[
0:used_frame_number, ]
current_index = self.buffer_size
self.i_remain_data = i_features[
used_frame_number:frame_number, ]
self.o_remain_data = o_features[
used_frame_number:frame_number, ]
self.remain_frame_number = frame_number - used_frame_number
self.file_index += 1
sftp.close()
i_temp_set = i_temp_set[0:current_index, ]
o_temp_set = o_temp_set[0:current_index, ]
numpy.random.seed(271639)
numpy.random.shuffle(i_temp_set)
numpy.random.seed(271639)
numpy.random.shuffle(o_temp_set)
i_shared_set = self.make_shared(i_temp_set, 'x')
o_shared_set = self.make_shared(o_temp_set, 'y')
io_shared_set = (i_shared_set, o_shared_set)
return io_shared_set, i_temp_set, o_temp_set
#src_aligned_lf0_dir = os.path.join(src_aligned_feat_dir, "lf0")
#if not os.path.exists(src_aligned_mag_dir):
# os.mkdir(src_aligned_mag_dir)
#if not os.path.exists(src_aligned_bap_dir):
# os.mkdir(src_aligned_bap_dir)
#if not os.path.exists(src_aligned_lf0_dir):
# os.mkdir(src_aligned_lf0_dir)
#################################################################
######## align source feats with target feats using dtw ## ######
#################################################################
io_funcs = BinaryIOCollection()
aligner = AlignFeats()
def get_mag_filelist(mag_dir):
mag_files = []
for file in os.listdir(mag_dir):
whole_filepath = os.path.join(mag_dir, file)
if os.path.isfile(whole_filepath) and str(whole_filepath).endswith(
".mag"):
mag_files.append(whole_filepath)
elif os.path.isdir(whole_filepath):
mag_files += get_mag_filelist(whole_filepath)
mag_files.sort()
def zeros(self, m, n):
if (n == 1):
arr = np.ndarray((m, ), float)
else:
arr = np.ndarray((m, n), float)
arr.fill(0)
return arr
if __name__ == "__main__":
dnn_dir = '/afs/inf.ed.ac.uk/group/cstr/projects/phd/s1432486/work/dnn_tts_blzpilot/'
label_align_dir = os.path.join(dnn_dir,
'two_stage_mtldnn/data/label_state_align')
htsclass = readHTSlabelFile()
io_funcs = BinaryIOCollection()
DFP = 1
if DFP:
parseLabFile = True
if parseLabFile:
filelist = os.path.join(dnn_dir,
'two_stage_mtldnn/data/file_id_list.scp')
list_of_files = io_funcs.load_file_list(filelist)
max_syl_dur = 0
max_syl_dur_filename = ''
for i in range(len(list_of_files)):
filename = list_of_files[i]
print filename
def __init__(self):
self.io_funcs = BinaryIOCollection()
def load_next_utterance(self):
print ("Loading Next Utterance")
i_temp_set = numpy.empty((self.buffer_size, self.n_ins))
o_temp_set = numpy.empty((self.buffer_size, self.n_outs))
io_function = BinaryIOCollection()
sftp = pysftp.Connection('eddie.ecdf.ed.ac.uk',username='******',password='******')
sftp.get(self.i_list[self.file_index])
sftp.get(self.o_list[self.file_index])
i_file_name = self.extract_file_id(self.i_list[self.file_index])
o_file_name = self.extract_file_id(self.o_list[self.file_index])
remove_items = []
while (os.path.isfile(i_file_name) and os.path.isfile(o_file_name)) is False:
print i_file_name," is :", os.path.isfile(i_file_name), "in load_next_utterance"
print o_file_name," is :", os.path.isfile(o_file_name), "in load_next_utterance"
remove_items.append(i_file_name)
remove_items.append(o_file_name)
self.file_index +=1
sftp.get(self.i_list[self.file_index])
sftp.get(self.o_list[self.file_index])
i_file_name = self.extract_file_id(self.i_list[self.file_index])
o_file_name = self.extract_file_id(self.o_list[self.file_index])
remove_items.append(i_file_name)
remove_items.append(o_file_name)
sftp.close()
i_features, lab_frame_number = io_function.load_binary_file_frame(i_file_name, self.n_ins)
o_features, out_frame_number = io_function.load_binary_file_frame(o_file_name, self.n_outs)
for item in remove_items:
if os.path.isfile(item) is True:
os.remove(item)
remove_items = []
frame_number = lab_frame_number
if abs(lab_frame_number - out_frame_number) < 5: ## we allow small difference here. may not be correct, but sometimes, there is one/two frames difference
if lab_frame_number > out_frame_number:
frame_number = out_frame_number
else:
print "The number of frames in label and acoustic features are different : ",lab_frame_number, " vs " , out_frame_number
raise
i_temp_set = o_features[0:frame_number, ]
o_temp_set = i_features[0:frame_number, ]
self.file_index += 1
if self.file_index >= self.list_size:
self.end_reading = True
self.file_index = 0
i_shared_set = self.make_shared(i_temp_set, 'x')
o_shared_set = self.make_shared(o_temp_set, 'y')
io_shared_set = (i_shared_set, o_shared_set)
return io_shared_set, i_temp_set, o_temp_set