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