SPPAS integration of the Phonetization automatic annotation.
Module sppas.src.annotations
Class sppasPhon
Description
Constructor
Create a sppasPhon instance without any linguistic resources.
Log is used for a better communication of the annotation process and its results. If None, logs are redirected to the default logging system.
Parameters
- log: (sppasLog) Human-readable logs.
View Source
def __init__(self, log=None):
"""Create a sppasPhon instance without any linguistic resources.
Log is used for a better communication of the annotation process and its
results. If None, logs are redirected to the default logging system.
:param log: (sppasLog) Human-readable logs.
"""
super(sppasPhon, self).__init__('phonetize.json', log)
self.__phonetizer = None
self.maptable = sppasMapping()
self.load_resources()
self.__lang = 'und'
Public functions
fix_options
Fix all options.
Available options are:
- phonunk
- usesstdtokens
Parameters
- options: (sppasOption)
View Source
def fix_options(self, options):
"""Fix all options.
Available options are:
- phonunk
- usesstdtokens
:param options: (sppasOption)
"""
for opt in options:
key = opt.get_key()
if key == 'phonunk':
self.set_unk(opt.get_value())
elif key == 'usestdtokens':
self.set_usestdtokens(opt.get_value())
elif 'pattern' in key:
self._options[key] = opt.get_value()
else:
raise AnnotationOptionError(key)
set_unk
Fix the unk option value.
Parameters
- unk: (bool) If unk is set to True, the system attempts to phonetize unknown entries (i.e. tokens missing in the dictionary). Otherwise, the phonetization of an unknown entry unit is set to the default stamp.
View Source
def set_unk(self, unk):
"""Fix the unk option value.
:param unk: (bool) If unk is set to True, the system attempts
to phonetize unknown entries (i.e. tokens missing in the dictionary).
Otherwise, the phonetization of an unknown entry unit is set to the
default stamp.
"""
self._options['phonunk'] = unk
set_usestdtokens
Fix the stdtokens option.
Parameters
- stdtokens: (bool) If it is set to True, the phonetization uses the standard transcription as input, instead of the faked transcription. This option does make sense only for an Enriched Orthographic Transcription.
View Source
def set_usestdtokens(self, stdtokens):
"""Fix the stdtokens option.
:param stdtokens: (bool) If it is set to True, the phonetization
uses the standard transcription as input, instead of the faked
transcription. This option does make sense only for an Enriched
Orthographic Transcription.
"""
self._options['usestdtokens'] = stdtokens
load_resources
Set the pronunciation dictionary and the mapping table.
Parameters
- dict_filename: (str) The pronunciation dictionary in HTK-ASCII format with UTF-8 encoding.
Parameters
- map_filename: (str) is the filename of a mapping table. It is used to generate new pronunciations by mapping phonemes of the dict.
Parameters
- lang: (str) Iso639-3 of the language or "und" if unknown.
View Source
def load_resources(self, dict_filename=None, map_filename=None, lang='und', **kwargs):
"""Set the pronunciation dictionary and the mapping table.
:param dict_filename: (str) The pronunciation dictionary in HTK-ASCII
format with UTF-8 encoding.
:param map_filename: (str) is the filename of a mapping table. It is used to generate new pronunciations by mapping phonemes of the dict.
:param lang: (str) Iso639-3 of the language or "und" if unknown.
"""
self.__lang = lang
if map_filename is not None:
self.maptable = sppasMapping(map_filename)
self.logfile.print_message(info(1160, 'annotations').format(len(self.maptable)), indent=0)
else:
self.maptable = sppasMapping()
pdict = sppasDictPron(dict_filename, nodump=False)
if dict_filename is not None:
self.__phonetizer = sppasDictPhonetizer(pdict, self.maptable)
self.logfile.print_message(info(1162, 'annotations').format(len(pdict)), indent=0)
else:
self.__phonetizer = sppasDictPhonetizer(pdict)
convert
Phonetize annotations of a tokenized tier.
Parameters
- tier: (Tier) the ortho transcription previously tokenized.
Returns
- (Tier) phonetized tier with name "Phones"
View Source
def convert(self, tier):
"""Phonetize annotations of a tokenized tier.
:param tier: (Tier) the ortho transcription previously tokenized.
:returns: (Tier) phonetized tier with name "Phones"
"""
if tier is None:
raise IOError('No given tier.')
if tier.is_empty() is True:
raise EmptyInputError(name=tier.get_name())
phones_tier = sppasTier('Phones')
phones_tier.set_meta('linguistic_resource_dict', self.__phonetizer.get_dict_filename())
tier.set_meta('language', '0')
for i, ann in enumerate(tier):
logging.info(info(1220, 'annotations').format(number=i + 1))
location = ann.get_location().copy()
labels = list()
normalized = list()
for label in ann.get_labels():
if ' ' in label:
normalized.extend(label.split())
else:
normalized.append(label)
for label in normalized:
phonetizations = list()
for text, score in label:
if text.is_pause() or text.is_silence():
phonetizations.append(SIL)
elif text.is_empty() is False:
phones = self._phonetize(text.get_content(), track_nb=i + 1)
for p in phones:
phonetizations.extend(p.split(separators.variants))
tags = [sppasTag(p) for p in set(phonetizations)]
labels.append(sppasLabel(tags))
phones_tier.create_annotation(location, labels)
return phones_tier
get_inputs
Return the the tier with aligned tokens.
Parameters
- input_files: (list)
Raises
NoTierInputError
Returns
- (sppasTier)
View Source
def get_inputs(self, input_files):
"""Return the the tier with aligned tokens.
:param input_files: (list)
:raise: NoTierInputError
:return: (sppasTier)
"""
tier = None
annot_ext = self.get_input_extensions()
tier_pattern = ''
if self._options['usestdtokens'] is True:
tier_pattern = 'std'
for filename in input_files:
if filename is None:
continue
fn, fe = os.path.splitext(filename)
if tier is None and fe in annot_ext[0]:
parser = sppasTrsRW(filename)
trs_input = parser.read()
tier = sppasFindTier.tokenization(trs_input, tier_pattern)
if tier is not None:
if self.logfile:
self.logfile.print_message('Input tier to be phonetized: {}'.format(tier.get_name()), indent=1)
return tier
logging.error('A tier with a normalized text was not found.')
raise NoTierInputError
run
Run the automatic annotation process on an input.
Parameters
- input_files: (list of str) Normalized text
- output: (str) the output name
Returns
- (sppasTranscription)
View Source
def run(self, input_files, output=None):
"""Run the automatic annotation process on an input.
:param input_files: (list of str) Normalized text
:param output: (str) the output name
:returns: (sppasTranscription)
"""
tier_input = self.get_inputs(input_files)
tier_phon = self.convert(tier_input)
trs_output = sppasTranscription(self.name)
trs_output.set_meta('annotation_result_of', input_files[0])
trs_output.set_meta('language_iso', 'iso639-3')
trs_output.set_meta('language_name_0', 'Undetermined')
if len(self.__lang) == 3:
trs_output.set_meta('language_code_0', self.__lang)
trs_output.set_meta('language_url_0', 'https://iso639-3.sil.org/code/' + self.__lang)
else:
trs_output.set_meta('language_code_0', 'und')
trs_output.set_meta('language_url_0', 'https://iso639-3.sil.org/code/und')
if tier_phon is not None:
trs_output.append(tier_phon)
if output is not None:
if len(trs_output) > 0:
output_file = self.fix_out_file_ext(output)
parser = sppasTrsRW(output_file)
parser.write(trs_output)
return [output_file]
else:
raise EmptyOutputError
return trs_output
get_output_pattern
Pattern this annotation uses in an output filename.
View Source
def get_output_pattern(self):
"""Pattern this annotation uses in an output filename."""
return self._options.get('outputpattern', '-phon')
get_input_patterns
Pattern this annotation expects for its input filename.
View Source
def get_input_patterns(self):
"""Pattern this annotation expects for its input filename."""
return [self._options.get('inputpattern', '-token')]
Private functions
_phonetize
Phonetize a text.
Because we absolutely need to match with the number of tokens, this method will always return a string: either the automatic phonetization (from dict or from phonunk) or the unk stamp.
Parameters
- entry: (str) The string to be phonetized.
Returns
- phonetization of the given entry
View Source
def _phonetize(self, entry, track_nb=0):
"""Phonetize a text.
Because we absolutely need to match with the number of tokens, this
method will always return a string: either the automatic phonetization
(from dict or from phonunk) or the unk stamp.
:param entry: (str) The string to be phonetized.
:returns: phonetization of the given entry
"""
unk = symbols.unk
tab = self.__phonetizer.get_phon_tokens(entry.split(), phonunk=self._options['phonunk'])
tab_phones = list()
for tex, p, s in tab:
message = None
if s == annots.error:
message = info(1110, 'annotations').format(tex) + info(1114, 'annotations')
self.logfile.print_message(message, indent=2, status=s)
return [unk]
else:
if s == annots.warning:
message = info(1110, 'annotations').format(tex)
if len(p) > 0:
message = message + info(1112, 'annotations').format(p)
else:
message = message + info(1114, 'annotations')
p = unk
tab_phones.append(p)
if message:
self.logfile.print_message(MSG_TRACK.format(number=track_nb), indent=1)
self.logfile.print_message(message, indent=2, status=s)
return tab_phones