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PaddleSpeech/deepspeech/decoders/swig/ctc_beam_search_decoder.h

78 lines
2.9 KiB

Support paddle 2.x (#538) * 2.x model * model test pass * fix data * fix soundfile with flac support * one thread dataloader test pass * export feasture size add trainer and utils add setup model and dataloader update travis using Bionic dist * add venv; test under venv * fix unittest; train and valid * add train and config * add config and train script * fix ctc cuda memcopy error * fix imports * fix train valid log * fix dataset batch shuffle shift start from 1 fix rank_zero_only decreator error close tensorboard when train over add decoding config and code * test process can run * test with decoding * test and infer with decoding * fix infer * fix ctc loss lr schedule sortagrad logger * aishell egs * refactor train add aishell egs * fix dataset batch shuffle and add batch sampler log print model parameter * fix model and ctc * sequence_mask make all inputs zeros, which cause grad be zero, this is a bug of LessThanOp add grad clip by global norm add model train test notebook * ctc loss remove run prefix using ord value as text id * using unk when training compute_loss need text ids ord id using in test mode, which compute wer/cer * fix tester * add lr_deacy refactor code * fix tools * fix ci add tune fix gru model bugs add dataset and model test * fix decoding * refactor repo fix decoding * fix musan and rir dataset * refactor io, loss, conv, rnn, gradclip, model, utils * fix ci and import * refactor model add export jit model * add deploy bin and test it * rm uselss egs * add layer tools * refactor socket server new model from pretrain * remve useless * fix instability loss and grad nan or inf for librispeech training * fix sampler * fix libri train.sh * fix doc * add license on cpp * fix doc * fix libri script * fix install * clip 5 wer 7.39, clip 400 wer 7.54, 1.8 clip 400 baseline 7.49
4 years ago
// Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#ifndef CTC_BEAM_SEARCH_DECODER_H_
#define CTC_BEAM_SEARCH_DECODER_H_
#include <string>
#include <utility>
#include <vector>
#include "scorer.h"
/* CTC Beam Search Decoder
* Parameters:
* probs_seq: 2-D vector that each element is a vector of probabilities
* over vocabulary of one time step.
* vocabulary: A vector of vocabulary.
* beam_size: The width of beam search.
* cutoff_prob: Cutoff probability for pruning.
* cutoff_top_n: Cutoff number for pruning.
* ext_scorer: External scorer to evaluate a prefix, which consists of
* n-gram language model scoring and word insertion term.
* Default null, decoding the input sample without scorer.
* Return:
* A vector that each element is a pair of score and decoding result,
* in desending order.
*/
std::vector<std::pair<double, std::string>> ctc_beam_search_decoder(
const std::vector<std::vector<double>> &probs_seq,
const std::vector<std::string> &vocabulary,
size_t beam_size,
double cutoff_prob = 1.0,
size_t cutoff_top_n = 40,
Scorer *ext_scorer = nullptr,
size_t blank_id = 0);
/* CTC Beam Search Decoder for batch data
* Parameters:
* probs_seq: 3-D vector that each element is a 2-D vector that can be used
* by ctc_beam_search_decoder().
* vocabulary: A vector of vocabulary.
* beam_size: The width of beam search.
* num_processes: Number of threads for beam search.
* cutoff_prob: Cutoff probability for pruning.
* cutoff_top_n: Cutoff number for pruning.
* ext_scorer: External scorer to evaluate a prefix, which consists of
* n-gram language model scoring and word insertion term.
* Default null, decoding the input sample without scorer.
* Return:
* A 2-D vector that each element is a vector of beam search decoding
* result for one audio sample.
*/
std::vector<std::vector<std::pair<double, std::string>>>
ctc_beam_search_decoder_batch(
const std::vector<std::vector<std::vector<double>>> &probs_split,
const std::vector<std::string> &vocabulary,
size_t beam_size,
size_t num_processes,
double cutoff_prob = 1.0,
size_t cutoff_top_n = 40,
Scorer *ext_scorer = nullptr,
size_t blank_id = 0);
#endif // CTC_BEAM_SEARCH_DECODER_H_