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PaddleSpeech/speechx/examples/decoder/decoder_test_main.cc

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// Copyright (c) 2022 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.
// todo refactor, repalce with gtest
#include "base/flags.h"
#include "base/log.h"
#include "decoder/ctc_beam_search_decoder.h"
#include "kaldi/util/table-types.h"
#include "nnet/decodable.h"
DEFINE_string(nnet_prob_respecifier, "", "test nnet prob rspecifier");
DEFINE_string(dict_file, "vocab.txt", "vocabulary of lm");
DEFINE_string(lm_path, "lm.klm", "language model");
using kaldi::BaseFloat;
using kaldi::Matrix;
using std::vector;
// test decoder by feeding nnet posterior probability
int main(int argc, char* argv[]) {
gflags::ParseCommandLineFlags(&argc, &argv, false);
google::InitGoogleLogging(argv[0]);
kaldi::SequentialBaseFloatMatrixReader likelihood_reader(
FLAGS_nnet_prob_respecifier);
std::string dict_file = FLAGS_dict_file;
std::string lm_path = FLAGS_lm_path;
LOG(INFO) << "dict path: " << dict_file;
LOG(INFO) << "lm path: " << lm_path;
int32 num_done = 0, num_err = 0;
ppspeech::CTCBeamSearchOptions opts;
opts.dict_file = dict_file;
opts.lm_path = lm_path;
ppspeech::CTCBeamSearch decoder(opts);
std::shared_ptr<ppspeech::Decodable> decodable(
new ppspeech::Decodable(nullptr, nullptr));
decoder.InitDecoder();
for (; !likelihood_reader.Done(); likelihood_reader.Next()) {
string utt = likelihood_reader.Key();
const kaldi::Matrix<BaseFloat> likelihood = likelihood_reader.Value();
LOG(INFO) << "process utt: " << utt;
LOG(INFO) << "rows: " << likelihood.NumRows();
LOG(INFO) << "cols: " << likelihood.NumCols();
decodable->Acceptlikelihood(likelihood);
decoder.AdvanceDecode(decodable);
std::string result;
result = decoder.GetFinalBestPath();
KALDI_LOG << " the result of " << utt << " is " << result;
decodable->Reset();
decoder.Reset();
++num_done;
}
KALDI_LOG << "Done " << num_done << " utterances, " << num_err
<< " with errors.";
return (num_done != 0 ? 0 : 1);
}