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117 lines
4.8 KiB
117 lines
4.8 KiB
"""Wrapper for various CTC decoders in SWIG."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import swig_decoders
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class Scorer(swig_decoders.Scorer):
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"""Wrapper for Scorer.
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:param alpha: Parameter associated with language model. Don't use
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language model when alpha = 0.
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:type alpha: float
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:param beta: Parameter associated with word count. Don't use word
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count when beta = 0.
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:type beta: float
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:model_path: Path to load language model.
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:type model_path: basestring
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"""
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def __init__(self, alpha, beta, model_path, vocabulary):
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swig_decoders.Scorer.__init__(self, alpha, beta, model_path, vocabulary)
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def ctc_greedy_decoder(probs_seq, vocabulary):
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"""Wrapper for ctc best path decoder in swig.
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:param probs_seq: 2-D list of probability distributions over each time
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step, with each element being a list of normalized
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probabilities over vocabulary and blank.
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:type probs_seq: 2-D list
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:param vocabulary: Vocabulary list.
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:type vocabulary: list
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:return: Decoding result string.
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:rtype: basestring
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"""
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return swig_decoders.ctc_greedy_decoder(probs_seq.tolist(), vocabulary)
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def ctc_beam_search_decoder(probs_seq,
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vocabulary,
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beam_size,
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cutoff_prob=1.0,
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cutoff_top_n=40,
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ext_scoring_func=None):
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"""Wrapper for the CTC Beam Search Decoder.
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:param probs_seq: 2-D list of probability distributions over each time
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step, with each element being a list of normalized
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probabilities over vocabulary and blank.
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:type probs_seq: 2-D list
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:param vocabulary: Vocabulary list.
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:type vocabulary: list
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:param beam_size: Width for beam search.
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:type beam_size: int
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:param cutoff_prob: Cutoff probability in pruning,
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default 1.0, no pruning.
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:type cutoff_prob: float
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:param cutoff_top_n: Cutoff number in pruning, only top cutoff_top_n
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characters with highest probs in vocabulary will be
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used in beam search, default 40.
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:type cutoff_top_n: int
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:param ext_scoring_func: External scoring function for
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partially decoded sentence, e.g. word count
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or language model.
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:type external_scoring_func: callable
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:return: List of tuples of log probability and sentence as decoding
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results, in descending order of the probability.
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:rtype: list
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"""
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return swig_decoders.ctc_beam_search_decoder(probs_seq.tolist(), vocabulary,
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beam_size, cutoff_prob,
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cutoff_top_n, ext_scoring_func)
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def ctc_beam_search_decoder_batch(probs_split,
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vocabulary,
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beam_size,
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num_processes,
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cutoff_prob=1.0,
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cutoff_top_n=40,
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ext_scoring_func=None):
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"""Wrapper for the batched CTC beam search decoder.
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:param probs_seq: 3-D list with each element as an instance of 2-D list
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of probabilities used by ctc_beam_search_decoder().
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:type probs_seq: 3-D list
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:param vocabulary: Vocabulary list.
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:type vocabulary: list
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:param beam_size: Width for beam search.
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:type beam_size: int
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:param num_processes: Number of parallel processes.
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:type num_processes: int
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:param cutoff_prob: Cutoff probability in vocabulary pruning,
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default 1.0, no pruning.
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:type cutoff_prob: float
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:param cutoff_top_n: Cutoff number in pruning, only top cutoff_top_n
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characters with highest probs in vocabulary will be
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used in beam search, default 40.
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:type cutoff_top_n: int
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:param num_processes: Number of parallel processes.
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:type num_processes: int
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:param ext_scoring_func: External scoring function for
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partially decoded sentence, e.g. word count
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or language model.
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:type external_scoring_function: callable
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:return: List of tuples of log probability and sentence as decoding
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results, in descending order of the probability.
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:rtype: list
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"""
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probs_split = [probs_seq.tolist() for probs_seq in probs_split]
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return swig_decoders.ctc_beam_search_decoder_batch(
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probs_split, vocabulary, beam_size, num_processes, cutoff_prob,
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cutoff_top_n, ext_scoring_func)
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