def predictLM(self):
""" Predict landmarks from generated phonemes."""
phns = self.get_tier('phones')
lm_tier = LMTier(name="predicted", xmin = self.xmin, xmax=self.xmax)
## g_tier = PointTier(name="g", xmin = self.xmin, xmax=self.xmax)
## n_tier = PointTier(name="v",xmin = self.xmin, xmax=self.xmax)
prev = Phoneme(0,0)
for phn in phns:
# generate landmark from phoneme pairs
lm=LMref.predict_table[LMref.phoneme_class(prev.text)][LMref.phoneme_class(phn.text)]
if lm!='':
lm_tier.insert(LMPoint(phn.xmin, lm))
## # glottalization
## if is_voiced(prev.text) and not is_voiced(phn):
## g_tier.insert(Point(phn.xmin, mark='-g'))
## elif is_voiced(phn) and not is_voiced(prev.text):
## g_tier.insert(Point(phn.xmin, mark='+g'))
## # velopharyngeal
## if is_nasal(prev.text) and not is_nasal(phn):
## n_tier.insert(Point(phn.xmin, mark='-n'))
## elif is_nasal(phn) and not is_nasal(prev.text):
## n_tier.insert(Point(phn.xmin, mark='+n'))
prev=phn
self.append(LMTier.lmTier(lm_tier).splitLMs())
return self.tiers[-1]
def predictLM(self):
""" Predict landmarks from generated phonemes."""
phns = self.get_tier('phones')
lm_tier = LMTier(name="predicted", xmin=self.xmin, xmax=self.xmax)
## g_tier = PointTier(name="g", xmin = self.xmin, xmax=self.xmax)
## n_tier = PointTier(name="v",xmin = self.xmin, xmax=self.xmax)
prev = Phoneme(0, 0)
for phn in phns:
# generate landmark from phoneme pairs
try:
lm = LMref.predict_table[LMref.phoneme_class(
prev.text)][LMref.phoneme_class(phn.text)]
except KeyError:
raise RuntimeError(LMref.phoneme_class(prev.text),
LMref.phoneme_class(phn.text), prev.text,
phn.text, phn.xmax)
if lm != '':
lm_tier.insert(LMPoint(phn.xmin, lm))
## # glottalization
## if is_voiced(prev.text) and not is_voiced(phn):
## g_tier.insert(Point(phn.xmin, mark='-g'))
## elif is_voiced(phn) and not is_voiced(prev.text):
## g_tier.insert(Point(phn.xmin, mark='+g'))
## # velopharyngeal
## if is_nasal(prev.text) and not is_nasal(phn):
## n_tier.insert(Point(phn.xmin, mark='-n'))
## elif is_nasal(phn) and not is_nasal(prev.text):
## n_tier.insert(Point(phn.xmin, mark='+n'))
prev = phn
self.append(LMTier.lmTier(lm_tier).splitLMs())
return self.tiers[-1]
def __init__(self, tmin, tmax, phn='#', t='', n=0, sn=0):
""" Default values corresponds to a silence interval. """
Interval.__init__(self, tmin, tmax, phn)
# manner class of the phoneme (string)
self.manner = LMref.phoneme_class(phn)
# Lexical stress (int)
try:
self.stress = int(phn[-1])
except:
self.stress = -1
# Syllabic position of phoneme
# Type (string)
self.type = t
# Number (int)
self.number = n
# Subnumber (int)
self.subnumber = sn
self.links = {}
def __init__(self, tmin, tmax, phn='#', t='', n=0, sn=0):
""" Default values corresponds to a silence interval. """
Interval.__init__(self, tmin, tmax, phn)
# manner class of the phoneme (string)
self.manner = LMref.phoneme_class(phn)
# Lexical stress (int)
try:
self.stress = int(phn[-1])
except:
self.stress = -1
# Syllabic position of phoneme
# Type (string)
self.type = t
# Number (int)
self.number = n
# Subnumber (int)
self.subnumber = sn
self.links = {}
