def read_walign(self, filename):
"""
Read an alignment file in the standard format of Julius CSR engine.
@param filename (str - IN) The input file name.
@return Two lists of tuples:
- None
- (start-time end-time word score)
"""
tokens = [""]
scores = [0]
_wordalign = []
wordidx = -1
with codecs.open(filename, "r", encoding) as fp:
lines = fp.readlines()
for line in lines:
# Each line is either a new annotation or nothing interesting!
line = ToStrip(line)
if line.startswith("=== begin forced alignment ==="):
wordidx = 0
elif line.startswith("=== end forced alignment ==="):
wordidx = -1
elif line.startswith("wseq1:"):
line = line[6:]
# each token
tokens = line.split()
if len(tokens) == 0:
tokens = [""]
elif line.startswith("cmscore1:"):
line = line[9:]
# confidence score of the pronunciation of each token
scores = [float(s) for s in line.split()]
if len(scores) == 0:
scores = [0]
elif line.startswith("[") and wordidx > -1:
# New phonemes
line = line.replace("[", "")
line = line.replace("]", "")
line = ToStrip(line)
tab = line.split(" ")
# tab 0: first frame
# tab 1: last frame
# tab 2: score of the segmentation (log proba)
# tab 3: word
loc_s = float(tab[0]) / 100.0
loc_e = float(tab[1]) / 100.0
_wordalign.append([loc_s, loc_e, tokens[wordidx], scores[wordidx]])
wordidx = wordidx + 1
# Adjust time values
for wordidx in range(len(_wordalign)):
# Fix the end of this annotation to the begin of the next one.
loc_e = _wordalign[wordidx][1]
if wordidx < (len(_wordalign) - 1):
nextloc_s = _wordalign[wordidx + 1][0]
else:
nextloc_s = 0.0
if loc_e < nextloc_s:
loc_e = nextloc_s
_wordalign[wordidx][1] = loc_e
return (None, _wordalign)
def read_palign(self, filename):
"""
Read an alignment file in the standard format of Julius CSR engine.
@param filename (str - IN) The input file name.
@return Two lists of tuples:
- (start-time end-time phoneme score)
- (start-time end-time word score)
"""
_phonalign = []
_wordalign = []
phonidx = -1 # phoneme index
loc_s = 0.0 # phoneme start time
loc_e = 0.0 # phoneme end time
phonlist = []
wordseq = []
scores = [0]
tokens = [""]
with codecs.open(filename, "r", encoding) as fp:
lines = fp.readlines()
for line in lines:
# Each line is either a new annotation or nothing interesting!
line = ToStrip(line)
if line.startswith("=== begin forced alignment ==="):
phonidx = 0
elif line.startswith("=== end forced alignment ==="):
phonidx = -1
elif line.startswith("phseq1:"):
line = line[7:]
line = ToStrip(line)
wordseq = line.split("|")
# get indexes of each word
wordlist = []
_idx = -1
for w in wordseq:
_wrdphseq = w.strip().split()
_idx += len(_wrdphseq)
wordlist.append(_idx)
# get the list of phonemes (without word segmentation)
line = line.replace("|", "")
line = ToStrip(line)
phonlist = line.split()
elif line.startswith("cmscore1:"):
line = line[9:]
# confidence score of the pronunciation of each token
scores = [float(s) for s in line.split()]
if len(scores) == 0:
scores = [0]
elif line.startswith("sentence1:"):
line = line[10:]
# each token
tokens = line.split()
if len(tokens) == 0:
tokens = [""]
elif line.startswith("[") and phonidx > -1:
# New phonemes
line = line.replace("[", "")
line = line.replace("]", "")
line = ToStrip(line)
tab = line.split(" ")
# tab 0: first frame
# tab 1: last frame
# tab 2: score of the segmentation (log proba)
# tab 3: triphone used
loc_s = float(tab[0]) / 100.0
loc_e = float(tab[1]) / 100.0
if len(tab) > 3:
# Put real phoneme instead of triphones
_phonalign.append([loc_s, loc_e, phonlist[phonidx], tab[2]])
else:
_phonalign.append([loc_s, loc_e, "", tab[2]])
phonidx = phonidx + 1
# Adjust time values and create wordalign
wordidx = 0 # word index
wordloc_s = 0.0 # word start time
loc_e = 0.0
nextloc_s = 0.0
for phonidx in range(len(_phonalign)):
# Fix the end of this annotation to the begin of the next one.
loc_e = _phonalign[phonidx][1]
if phonidx < (len(_phonalign) - 1):
nextloc_s = _phonalign[phonidx + 1][0]
else:
nextloc_s = 0.0
if loc_e < nextloc_s:
loc_e = nextloc_s
_phonalign[phonidx][1] = loc_e
# Override the segmentation score of the phone by
# the score of the pronunciation of the word
_phonalign[phonidx][3] = scores[wordidx]
# add also the word?
if phonidx == wordlist[wordidx]:
_wordalign.append([wordloc_s, loc_e, tokens[wordidx], scores[wordidx]])
wordidx = wordidx + 1
wordloc_s = loc_e
# last word, or the only entry in case of empty interval...
if len(wordseq) - 1 == wordidx:
_wordalign.append([wordloc_s, loc_e, tokens[wordidx - 1], scores[wordidx - 1]])
return (_phonalign, _wordalign)
