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135 lines
5.6 KiB
135 lines
5.6 KiB
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Wrapper for various CTC decoders in SWIG."""
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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: str
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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, blank_id):
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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: str
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"""
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result = swig_decoders.ctc_greedy_decoder(probs_seq.tolist(), vocabulary,
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blank_id)
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return result
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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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blank_id=0):
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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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beam_results = swig_decoders.ctc_beam_search_decoder(
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probs_seq.tolist(), vocabulary, beam_size, cutoff_prob, cutoff_top_n,
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ext_scoring_func, blank_id)
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beam_results = [(res[0], res[1].decode('utf-8')) for res in beam_results]
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return beam_results
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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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blank_id=0):
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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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batch_beam_results = 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, blank_id)
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batch_beam_results = [[(res[0], res[1]) for res in beam_results]
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for beam_results in batch_beam_results]
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return batch_beam_results
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