def ctc_beam_search_decoder(probs_seq,
vocabulary,
beam_size,
cutoff_prob=1.0,
cutoff_top_n=40,
ext_scoring_func=None):
"""Wrapper for the CTC Beam Search Decoder.
:param probs_seq: 2-D list of probability distributions over each time
step, with each element being a list of normalized
probabilities over vocabulary and blank.
:type probs_seq: 2-D list
:param vocabulary: Vocabulary list.
:type vocabulary: list
:param beam_size: Width for beam search.
:type beam_size: int
:param cutoff_prob: Cutoff probability in pruning,
default 1.0, no pruning.
:type cutoff_prob: float
:param cutoff_top_n: Cutoff number in pruning, only top cutoff_top_n
characters with highest probs in vocabulary will be
used in beam search, default 40.
:type cutoff_top_n: int
:param ext_scoring_func: External scoring function for
partially decoded sentence, e.g. word count
or language model.
:type external_scoring_func: callable
:return: List of tuples of log probability and sentence as decoding
results, in descending order of the probability.
:rtype: list
"""
beam_results = decoders_deprecated.ctc_beam_search_decoder(
probs_seq.tolist(), beam_size, vocabulary, cutoff_prob, cutoff_top_n,
ext_scoring_func)
beam_results = [(res[0], res[1].decode('utf-8')) for res in beam_results]
return beam_results
def test_beam_search_decoder_2(self):
beam_result = decoder.ctc_beam_search_decoder(
probs_seq=self.probs_seq2,
beam_size=self.beam_size,
vocabulary=self.vocab_list)
self.assertEqual(beam_result[0][1], self.beam_search_result[1])