def test_remove_stop_words():
from utilities.nlp_options import NLPOptions
options = NLPOptions()
data = "This is the way the world ends, not with a bang but with a whimper"
expected = " This way world ends bang whimper"
results = options.remove_stop_words(data)
assert results == expected
def test_apply_stemming():
from utilities.nlp_options import NLPOptions
options = NLPOptions()
data = 'the quick brown fox jumped over the lazy dog'
expected = 'the quick brown fox jump over the lazi dog '
result = options.apply_stemming(data)
assert result == expected
def test_expand_contractions_isnt():
from utilities.nlp_options import NLPOptions
options = NLPOptions()
expected = "is not"
data = "isn't"
result = options.expand_contractions(data)
assert result == expected
def test_convert_numbers_to_words():
from utilities.nlp_options import NLPOptions
options = NLPOptions()
data = '10'
expected = ' ten'
result = options.convert_numbers_to_words(data)
assert result == expected
def test_expand_contractions_yall():
from utilities.nlp_options import NLPOptions
options = NLPOptions()
expected = "you all"
data = "y'all"
result = options.expand_contractions(data)
assert result == expected
def test_apply_nlp_options_stop():
from utilities.nlp_options import NLPOptions
from model.nlp import NLPModel
hyp = 'thingy in the dancing'
options = NLPOptions()
model = NLPModel()
model.set_remove_stop_words(True)
result = options.apply_nlp_options(model, hyp)
expected = ' thingy dancing'
assert result == expected
def test_apply_nlp_options_stem():
from utilities.nlp_options import NLPOptions
from model.nlp import NLPModel
hyp = 'thingy dancing'
options = NLPOptions()
model = NLPModel()
model.set_apply_stemming(True)
result = options.apply_nlp_options(model, hyp)
expected = 'thingi danc '
assert result == expected
def test_apply_nlp_options_n2w():
from utilities.nlp_options import NLPOptions
from model.nlp import NLPModel
hyp = '34 567'
options = NLPOptions()
model = NLPModel()
model.set_n2w(True)
result = options.apply_nlp_options(model, hyp)
expected = ' thirty-four five hundred and sixty-seven'
assert result == expected
def test_apply_nlp_options_expand_cont():
from utilities.nlp_options import NLPOptions
from model.nlp import NLPModel
hyp = "isn't can't"
options = NLPOptions()
model = NLPModel()
model.set_expand_contractions(True)
result = options.apply_nlp_options(model, hyp)
expected = 'is not cannot'
assert result == expected
def test_apply_nlp_options_stem_exp():
from utilities.nlp_options import NLPOptions
from model.nlp import NLPModel
hyp = "thingy dancing won't"
options = NLPOptions()
model = NLPModel()
model.set_apply_stemming(True)
model.set_expand_contractions(True)
result = options.apply_nlp_options(model, hyp)
expected = 'thingi danc will not '
assert result == expected
def test_apply_nlp_options_n2w_exp():
from utilities.nlp_options import NLPOptions
from model.nlp import NLPModel
hyp = "666 don't"
options = NLPOptions()
model = NLPModel()
model.set_n2w(True)
model.set_expand_contractions(True)
result = options.apply_nlp_options(model, hyp)
expected = ' six hundred and sixty-six do not'
assert result == expected
def test_apply_nlp_options_stop_n2w():
from utilities.nlp_options import NLPOptions
from model.nlp import NLPModel
hyp = "in the 666"
options = NLPOptions()
model = NLPModel()
model.set_remove_stop_words(True)
model.set_n2w(True)
result = options.apply_nlp_options(model, hyp)
expected = ' six hundred sixtysix'
assert result == expected
def test_stem_stop_n2w():
from utilities.nlp_options import NLPOptions
from model.nlp import NLPModel
hyp = "don't in the won't didn't isn't raining 3 6 9"
options = NLPOptions()
model = NLPModel()
model.set_n2w(True)
model.set_remove_stop_words(True)
model.set_apply_stemming(True)
result = options.apply_nlp_options(model, hyp)
expected = 'nt wo nt nt nt rain three six nine '
assert result == expected
def test_stem_stop_exp():
from utilities.nlp_options import NLPOptions
from model.nlp import NLPModel
hyp = "don't in the won't didn't isn't raining"
options = NLPOptions()
model = NLPModel()
model.set_expand_contractions(True)
model.set_remove_stop_words(True)
model.set_apply_stemming(True)
result = options.apply_nlp_options(model, hyp)
expected = 'rain '
assert result == expected
def test_stem_stop_n2w():
from utilities.nlp_options import NLPOptions
from model.nlp import NLPModel
hyp = "666 don't in the raining"
options = NLPOptions()
model = NLPModel()
model.set_n2w(True)
model.set_remove_stop_words(True)
model.set_apply_stemming(True)
result = options.apply_nlp_options(model, hyp)
expected = 'six hundr sixtysix nt rain '
assert result == expected
def test_nlp_options_init():
from utilities.nlp_options import NLPOptions
options = NLPOptions()
result = options.contractions
assert isinstance(result, dict)
for value in result.values():
assert isinstance(value, str)
parser.add_argument('-p', '--phrase_file', required=False, type=str,
help='Path to file containing comma separated phrases')
parser.add_argument('-b', '--boosts', default=list(), nargs='+', required=False,
help=('Space separated list of boost values to evaluate for speech adaptation'))
parser.add_argument('-ch', '--multi', required=False, type=int,
help='Integer indicating the number of channels if more than one')
parser.add_argument('-q', '--random_queue', required=False, action='store_true', help='Replaces default queue.txt with randomly named queue file')
parser.add_argument('-fake', '--fake_hyp', required=False, action='store_true', help='Use a fake hypothesis for testing')
parser.add_argument('-limit', '--limit', required=False, default=None,type= int, help = 'Limit to X number of audio files')
parser.add_argument('-nzb', '--no_zeros_boost', required=False, action='store_true', help='skip boost of 0' )
parser.add_argument('-single', '--single_word', required=False, action='store_true', help='process each letter rather than whole words')
parser.add_argument('-lf','--local_files_path', required=False, type=str, help='process local files', default=None)
nlp_model = NLPModel()
io_handler = IOHandler()
nlp_options = NLPOptions()
configuration = Configuration()
# Turn on punctuation .. why not.. no bearing on WER
configuration.set_enableAutomaticPunctuation(True)
args = parser.parse_args()
no_zeros_for_boost = args.no_zeros_boost
process_each_letter = args.single_word
local_files_path = args.local_files_path
limit = args.limit
cloud_store_uri = args.cloud_store_uri
io_handler.set_result_path(args.local_results_path)
only_transcribe = args.transcriptions_only
nlp_model.set_n2w(args.numbers_to_words)
nlp_model.set_apply_stemming(args.stem)
nlp_model.set_remove_stop_words(args.remove_stop_words)
