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hyphenation = title
ipa_cnt += 1
logging.info(u"%7d %7d %s IPA: %s" % (article_cnt, ipa_cnt, title, ipa))
dictf.write('%s;%s\n' % (hyphenation, ipa))
if ARTICLE_LIMIT and article_cnt >= ARTICLE_LIMIT:
logging.warn('DEBUG limit of %d reached -> exit.' % ARTICLE_LIMIT)
sys.exit(0)
#
# init
#
misc.init_app(PROC_TITLE)
#
# command line
#
parser = OptionParser("usage: %%prog [options]")
parser.add_option ("-l", "--lang", dest="lang", type = "str", default="de",
help="language (default: de)")
parser.add_option("-v", "--verbose", action="store_true", dest="verbose",
help="enable debug output")
(options, args) = parser.parse_args()
if options.verbose:
for lang in LANGUAGES:
s += '%3s:%9d (%5.1f%%)' % (lang, stats[m][lang], stats[m][lang]*100.0/totals[lang])
stats2.append((s, stats[m]['en']))
for t in sorted(stats2, key=lambda tup: tup[1]):
logging.info(t[0])
logging.getLogger().setLevel(DEFAULT_LOGLEVEL)
#
# init terminal
#
misc.init_app('ai_cli')
#
# logging
#
logging.basicConfig(level=DEFAULT_LOGLEVEL)
logging.getLogger("requests").setLevel(logging.WARNING)
#
# run cli
#
aicli = AICli()
sys.exit(aicli.main(loop=cmdln.LOOP_IF_EMPTY))
from optparse import OptionParser
from StringIO import StringIO
from nltools import misc
from nltools.tokenizer import tokenize
from speech_transcripts import Transcripts
WORKDIR = 'data/dst/speech/%s/deepspeech'
PROMPT_AUDIO_FACTOR = 1000
#
# init
#
misc.init_app ('speech_deepspeech_export')
config = misc.load_config ('.speechrc')
#
# commandline parsing
#
parser = OptionParser("usage: %prog [options] )")
parser.add_option ("-d", "--debug", dest="debug", type='int', default=0,
help="limit number of transcripts (debug purposes only), default: 0 (unlimited)")
parser.add_option ("-l", "--lang", dest="lang", type = "str", default='de',
help="language (default: de)")
parser.add_option ("-v", "--verbose", action="store_true", dest="verbose",
help="enable verbose logging")
publish_state(client)
except KeyboardInterrupt:
raise
except:
logging.error('EXCEPTION CAUGHT %s' % traceback.format_exc())
finally:
msg_cond.release()
#
# init
#
misc.init_app(PROC_TITLE)
#
# config, cmdline
#
config = misc.load_config('.airc', defaults = DEFAULTS)
broker_host = config.get ('mqtt', 'broker_host')
broker_port = config.getint ('mqtt', 'broker_port')
broker_user = config.get ('mqtt', 'broker_user')
broker_pw = config.get ('mqtt', 'broker_pw')
ai_model = config.get ('server', 'model')
lang = config.get ('server', 'lang')
vf_login = config.get ('server', 'vf_login')
rec_dir = config.get ('server', 'rec_dir')
import codecs
import traceback
import logging
import csv
from optparse import OptionParser
from nltools import misc
PROC_TITLE = 'moz_de_to_vf'
DEFAULT_NUM_CPUS = 12
#
# init terminal
#
misc.init_app (PROC_TITLE)
#
# command line
#
parser = OptionParser("usage: %prog [options]")
parser.add_option ("-n", "--num-cpus", dest="num_cpus", type="int", default=DEFAULT_NUM_CPUS,
help="number of cpus to use in parallel, default: %d" % DEFAULT_NUM_CPUS)
parser.add_option ("-v", "--verbose", action="store_true", dest="verbose",
help="enable debug output")
(options, args) = parser.parse_args()
if options.verbose:
import numpy as np
from optparse import OptionParser
from nltools import misc
WORKDIR = 'data/dst/asr-models/kaldi/segmentation'
SAMPLE_RATE = 16000
#
# init
#
misc.init_app ('abook-kaldi-retrieve')
config = misc.load_config ('.speechrc')
#
# commandline parsing
#
parser = OptionParser("usage: %prog [options] srcdir")
parser.add_option ("-v", "--verbose", action="store_true", dest="verbose",
help="enable verbose logging")
(options, args) = parser.parse_args()
if options.verbose:
logging.basicConfig(level=logging.DEBUG)
import logging
import json
from optparse import OptionParser
from nltools import misc
PROC_TITLE = 'import_mailabs'
DEFAULT_NUM_CPUS = 12
GENDERS = set(['male', 'female'])
#
# init
#
misc.init_app(PROC_TITLE)
#
# commandline
#
parser = OptionParser("usage: %prog [options]")
parser.add_option ("-n", "--num-cpus", dest="num_cpus", type="int", default=DEFAULT_NUM_CPUS,
help="number of cpus to use in parallel, default: %d" % DEFAULT_NUM_CPUS)
parser.add_option ("-v", "--verbose", action="store_true", dest="verbose",
help="verbose output")
(options, args) = parser.parse_args()
if options.verbose:
from nltools import misc
from nltools.tokenizer import tokenize
from nltools.phonetics import ipa2xsampa, xsampa2ipa
from nltools.sequiturclient import sequitur_gen_ipa
from speech_transcripts import Transcripts
from speech_lexicon import Lexicon
SEQUITUR_MODEL = 'data/models/sequitur-%s-latest'
#
# init
#
misc.init_app ('speech_lex_missing')
#
# command line
#
parser = OptionParser("usage: %prog [options] [filter] lex corpus")
parser.add_option ("-g", "--generate", action="store_true", dest="generate",
help="generate phoneme transcriptions using sequitur g2p")
parser.add_option ("-l", "--lang", dest="lang", type = "str", default='de',
help="language (default: de)")
parser.add_option ("-n", "--num-words", dest="num_words", type="int", default=50,
help="max number of missing words to report, default: 50")
from nltools.phonetics import ipa2xsampa
from speech_lexicon import Lexicon
from speech_transcripts import Transcripts
APP_NAME = 'speech_wav2letter_export'
LANGUAGE_MODELS_DIR = 'data/dst/lm'
ASR_MODELS_DIR = 'data/dst/asr-models'
#
# main
#
misc.init_app(APP_NAME)
#
# commandline
#
parser = OptionParser("usage: %prog [options] [ ... ]")
parser.add_option ("-d", "--debug", dest="debug", type='int', default=0, help="Limit number of sentences (debug purposes only), default: 0")
parser.add_option ("-l", "--lang", dest="lang", type = "str", default='de', help="language (default: de)")
parser.add_option ("-p", "--prompt-words", action="store_true", dest="prompt_words", help="Limit dict to tokens covered in prompts")
parser.add_option ("-v", "--verbose", action="store_true", dest="verbose", help="verbose output")
(options, args) = parser.parse_args()
import codecs
import re
import logging
from optparse import OptionParser
from nltools import misc
PROC_TITLE='librispeech_to_vf'
SUBSETS = set(['dev-clean', 'test-clean', 'train-clean-100', 'train-clean-360'])
#
# init
#
misc.init_app(PROC_TITLE)
#
# commandline
#
parser = OptionParser("usage: %prog [options]")
parser.add_option ("-v", "--verbose", action="store_true", dest="verbose",
help="verbose output")
(options, args) = parser.parse_args()
if options.verbose:
logging.basicConfig(level=logging.DEBUG)
else:
logging.basicConfig(level=logging.INFO)