def _decode_cnn_ctc_parse_args(args, logger):
parser = KaldiParser(
description=decode_cnn_ctc.__doc__,
add_verbose=True,
logger=logger,
)
# any boolean configuration should be kaldi-like
# (e.g. --strict=true)
parser.register('type', bool, kaldi_bool_arg_type)
parser.add_argument('data_rspecifier',
type='kaldi_rspecifier',
help='rspecifier to read in audio features to decode')
parser.add_argument('output_wspecifier',
type='kaldi_wspecifier',
help='wspecifier to write decoded sequences to')
parser.add_argument(
'label_to_id_map_path',
help='Where the file that converts labels to ids is stored.')
# we add all three sets of arguments as we allow them in the same
# config file - we just ignore what we don't want
ModelConfig().add_arguments_to_parser(parser)
TrainConfig().add_arguments_to_parser(parser)
DecodeConfig().add_arguments_to_parser(parser)
options = parser.parse_args(args)
return options
def _compute_error_rate_parse_args(args, logger):
parser = KaldiParser(
description=compute_error_rate.__doc__,
add_verbose=True,
logger=logger,
)
parser.add_argument(
'ref_rspecifier', type='kaldi_rspecifier',
help='Rspecifier pointing to reference (gold standard) transcriptions')
parser.add_argument(
'hyp_rspecifier', type='kaldi_wspecifier',
help='Rspecifier pointing to hypothesis transcriptions')
parser.add_argument(
'out_path', nargs='?', default=None,
help='Path to print results to. Default is stdout.')
parser.add_argument(
'--print-tables', type='kaldi_bool', default=False,
help='If set, will print breakdown of insertions, deletions, and subs '
'to out_path')
parser.add_argument(
'--strict', type='kaldi_bool', default=False,
help='If set, missing utterances will cause an error')
parser.add_argument(
'--insertion-cost', type=int, default=1,
help='Cost (in terms of edit distance) to perform an insertion')
parser.add_argument(
'--deletion-cost', type=int, default=1,
help='Cost (in terms of edit distance) to perform a deletion')
parser.add_argument(
'--substitution-cost', type=int, default=1,
help='Cost (in terms of edit distance) to perform a substitution')
parser.add_argument(
'--include-inserts-in-cost', type='kaldi_bool', default=True,
help='Whether to include insertions in error rate calculations')
parser.add_argument(
'--report-accuracy', type='kaldi_bool', default=False,
help='Whether to report accuracy (1 - error_rate) instead of '
'the error rate'
)
options = parser.parse_args(args)
return options
def _normalize_feat_lens_parse_args(args, logger):
parser = KaldiParser(
description=normalize_feat_lens.__doc__,
add_verbose=True,
logger=logger,
)
parser.add_argument(
'feats_in_rspecifier',
type='kaldi_rspecifier',
help='The features to be normalized',
)
parser.add_argument(
'len_in_rspecifier',
type='kaldi_rspecifier',
help='The reference lengths (int32 table)',
)
parser.add_argument(
'feats_out_wspecifier',
type='kaldi_wspecifier',
help='The output features',
)
parser.add_argument(
'--type',
type='kaldi_dtype',
default='bm',
help='The kaldi type of the input/output features',
)
parser.add_argument('--tolerance',
type=int,
default=float('inf'),
help='''\
How many frames deviation from reference to tolerate before error. The default
is to be infinitely tolerant (a feat I'm sure we all desire)
''')
parser.add_argument('--strict',
type='kaldi_bool',
default=False,
help='''\
Whether missing keys in len_in and lengths beyond the threshold cause
an error (true) or are skipped with a warning (false)
''')
parser.add_argument('--pad-mode',
default='edge',
choices=('zero', 'constant', 'edge', 'symmetric',
'mean'),
help='''\
If frames are being padded to the features, specify how they should be padded.
zero=zero pad, edge=pad with rightmost frame, symmetric=pad with reverse of
frame edges, mean=pad with mean feature values
''')
parser.add_argument('--side',
default='right',
choices=('left', 'right', 'center'),
help='''\
If an utterance needs to be padded or truncated, specify what side of the
utterance to do this on. left=beginning, right=end, center=distribute
evenly on either side
''')
return parser.parse_args(args)