def flatten_pattern(input_dictionary, input_mlf, output_dictionary,
output_mlf):
split_token = 'p'
H = HTK()
H.readMLF(input_mlf, ['sil', 'sp', '<s>', '</s>'])
H.readDCT(input_dictionary, ['sil', 'sp', '<s>', '</s>'])
M = open(output_mlf, 'w')
M.write('#!MLF!#\n')
for wav in H.wav_list:
M.write('"*/{}.rec"\n'.format(wav))
for word in H.wav2word[wav]:
#print word
beg = int(word[1])
end = int(word[2])
pro = int(word[3])
p_list = word[0].split(split_token)[1:]
p_count = len(p_list)
delta = 1.0 * (end - beg) / p_count
p_beg = [int(beg + delta * i) for i in range(p_count)]
p_end = [int(beg + delta * (i + 1)) for i in range(p_count)]
p_pro = []
for i in range(p_count):
p_pro.append(pro / p_count)
for i in range(p_count):
if p_list[i] == '': continue
M.write(str(p_beg[i]) + ' ')
M.write(str(p_end[i]) + ' ')
M.write(split_token + p_list[i] + ' ')
M.write(str(p_pro[i]))
M.write('\n')
M.write('.\n')
F = HTK()
F.word_list = []
F.word2pone = dict({})
F.pone2word = dict({})
for pone in H.pone2word:
#print pone
for p in pone:
if p in F.word_list: continue
F.word_list.append(p)
F.pone2word[p, ] = p
F.word2pone[p] = p,
F.writeDCT(output_dictionary, ['sil', 'sp'])
def flatten_pattern(input_dictionary, input_mlf, output_dictionary, output_mlf):
split_token = 'p'
H = HTK()
H.readMLF(input_mlf, ['sil', 'sp', '<s>', '</s>'])
H.readDCT(input_dictionary, ['sil', 'sp', '<s>', '</s>'])
M = open(output_mlf, 'w')
M.write('#!MLF!#\n')
# print H.wavList
for wav in H.wav_list:
M.write('"*/{}.rec"\n'.format(wav))
for word in H.wav2word[wav]:
# print word
beg = int(word[1])
end = int(word[2])
pro = int(word[3])
p_list = word[0].split(split_token)[1:]
p_count = len(p_list)
delta = 1.0 * (end - beg) / p_count
p_beg = [int(beg + delta * i) for i in range(p_count)]
p_end = [int(beg + delta * (i + 1)) for i in range(p_count)]
p_pro = []
for i in range(p_count):
p_pro.append(pro / p_count)
for i in range(p_count):
if p_list[i] == '': continue
M.write(str(p_beg[i]) + ' ')
M.write(str(p_end[i]) + ' ')
M.write(split_token + p_list[i] + ' ')
M.write(str(p_pro[i]))
M.write('\n')
M.write('.\n')
F = HTK()
F.word_list = []
F.word2pone = dict({})
F.pone2word = dict({})
for pone in H.pone2word:
for p in pone:
if p in F.word_list: continue
F.word_list.append(p)
F.pone2word[p,] = p
F.word2pone[p] = p,
F.writeDCT(output_dictionary, ['sil', 'sp'])
def parse_pattern(input_dictionary, input_mlf, output_dictionary, N=2):
def avg_dict(count_dict):
tot_con, avg_con = 0, 0
for phrase in count_dict:
tot_con += count_dict[phrase]
avg_con += 1
print tot_con, avg_con, tot_con / avg_con
return 1.0 * tot_con / avg_con
def add_phrase(phrase):
if phrase in p2w: return
word = ''
for phone in phrase:
word += str(phone)
w2p[word] = phrase
p2w[phrase] = word
wdl.append(word)
def entropy(v):
s = sum(v)
v = [float(p) / s for p in v]
H = 0
for p in v:
H -= p * math.log(p, 2)
return H
count_dict = parse_pattern_load_count(input_mlf, input_dictionary, N)
cond_dict_tail = ({})
cond_dict_head = ({})
for phrase in count_dict:
try:
cond_dict_tail[phrase[:-1]].append(count_dict[phrase])
except:
cond_dict_tail[phrase[:-1]] = [count_dict[phrase]]
try:
cond_dict_head[phrase[1:]].append(count_dict[phrase])
except:
cond_dict_head[phrase[1:]] = [count_dict[phrase]]
entropy_head = ({})
entropy_tail = ({})
for phrase in count_dict:
if phrase not in cond_dict_tail or phrase not in cond_dict_head: continue
entropy_tail[phrase] = entropy(cond_dict_tail[phrase])
entropy_head[phrase] = entropy(cond_dict_head[phrase])
thr_count = avg_dict(count_dict) * 5
thr_head = avg_dict(entropy_head)
thr_tail = avg_dict(entropy_tail)
w2p = dict({})
p2w = dict({})
wdl = []
for phrase in count_dict:
if phrase in entropy_tail and phrase in entropy_tail:
if entropy_head[phrase] > thr_head and entropy_tail[phrase] > thr_tail and count_dict[phrase] > thr_count:
add_phrase(tuple(phrase))
A = HTK()
A.word2pone = w2p
A.pone2word = p2w
A.word_list = wdl
A.writeDCT(output_dictionary, ['sil', 'sp'])
def parse_pattern(input_dictionary, input_mlf, output_dictionary):
def avg_dict(count_dict):
tot_con, avg_con = 0, 0
for phrase in count_dict:
tot_con += count_dict[phrase]
avg_con += 1
print tot_con, avg_con, tot_con / avg_con
return 1.0 * tot_con / avg_con
def add_phrase(phrase):
if phrase in p2w: return
word = ''
for phone in phrase:
word += str(phone)
w2p[word] = phrase
p2w[phrase] = word
wdl.append(word)
def entropy(v):
s = sum(v)
v = [float(p) / s for p in v]
H = 0
for p in v:
H -= p * math.log(p, 2)
return H
count_dict = parse_pattern_load_count(input_mlf, input_dictionary)
cond_dict_tail = ({})
cond_dict_head = ({})
for phrase in count_dict:
try:
cond_dict_tail[phrase[:-1]].append(count_dict[phrase])
except:
cond_dict_tail[phrase[:-1]] = [count_dict[phrase]]
try:
cond_dict_head[phrase[1:]].append(count_dict[phrase])
except:
cond_dict_head[phrase[1:]] = [count_dict[phrase]]
entropy_head = ({})
entropy_tail = ({})
for phrase in count_dict:
if phrase not in cond_dict_tail or phrase not in cond_dict_head:
continue
entropy_tail[phrase] = entropy(cond_dict_tail[phrase])
entropy_head[phrase] = entropy(cond_dict_head[phrase])
thr_count = avg_dict(count_dict) * 5
thr_head = avg_dict(entropy_head)
thr_tail = avg_dict(entropy_tail)
w2p = dict({})
p2w = dict({})
wdl = []
for phrase in count_dict:
if phrase in entropy_tail and phrase in entropy_tail:
if entropy_head[phrase] > thr_head and entropy_tail[
phrase] > thr_tail and count_dict[phrase] > thr_count:
add_phrase(tuple(phrase))
A = HTK()
A.word2pone = w2p
A.pone2word = p2w
A.word_list = wdl
A.writeDCT(output_dictionary, ['sil', 'sp'])
