def __init__(self, modeldir):
"""
Constructor.
HviteAligner aligns one inter-pausal unit.
@param modeldir (str) the acoustic model file name
"""
BaseAligner.__init__(self, modeldir)
self._outext = DEFAULT_EXT_OUT
def __init__(self, modeldir):
"""
Constructor.
BasicAlign aligns one inter-pausal unit with the same duration
for each phoneme. It selects the shortest in case of variants.
@param modeldir (str) the acoustic model file name
"""
BaseAligner.__init__(self, modeldir)
self._outext = DEFAULT_EXT_OUT
def __init__(self, modeldir):
"""
JuliusAligner is able to align one audio segment that can be:
- an inter-pausal unit,
- an utterance,
- a sentence...
no longer that a few seconds.
Things needed to run JuliusAligner:
To perform speech segmentation with Julius, three "models" have to be
prepared. The models should define the linguistic property of the
language: recognition unit, audio properties of the unit and the
linguistic constraint for the connection between the units.
Typically the unit should be a word, and you should give Julius these
models below:
1. "Acoustic model", which is a stochastic model of input waveform
patterns, typically per phoneme. Format is HTK-ASCII model.
2. "Word dictionary", which defines vocabulary.
3. "Language model", which defines syntax level rules that defines the
connection constraint between words. It should give the constraint for
the acceptable or preferable sentence patterns. It can be:
* either a rule-based grammar,
* or probabilistic N-gram model.
This class automatically construct the word dictionary and the language
model from both:
- the tokenization of speech,
- the phonetization of speech.
If outext is set to "palign", JuliusAligner will use a grammar and
it will produce both phones and words alignments.
If outext is set to "walign", JuliusAligner will use a slm and will
produce words alignments only.
@param modelfildir (str) the acoustic model file name
"""
BaseAligner.__init__(self, modeldir)
self._outext = DEFAULT_EXT_OUT
