Yang Zhou
3 years ago
parent
1133540682
commit
dc8efca272
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#!/bin/bash
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set +x
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set -e
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. path.sh
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# 1. compile
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if [ ! -d ${SPEECHX_EXAMPLES} ]; then
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pushd ${SPEECHX_ROOT}
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bash build.sh
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popd
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fi
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# input
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mkdir -p data
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data=$PWD/data
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ckpt_dir=$data/model
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model_dir=$ckpt_dir/exp/deepspeech2_online/checkpoints/
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vocb_dir=$ckpt_dir/data/lang_char
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# output
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aishell_wav_scp=aishell_test.scp
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if [ ! -d $data/test ]; then
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pushd $data
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wget -c https://paddlespeech.bj.bcebos.com/s2t/paddle_asr_online/aishell_test.zip
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unzip aishell_test.zip
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popd
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realpath $data/test/*/*.wav > $data/wavlist
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awk -F '/' '{ print $(NF) }' $data/wavlist | awk -F '.' '{ print $1 }' > $data/utt_id
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paste $data/utt_id $data/wavlist > $data/$aishell_wav_scp
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fi
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export GLOG_logtostderr=1
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# websocket client
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websocket_client_main \
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--wav_rspecifier=scp:$data/$aishell_wav_scp --streaming_chunk=0.36
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#!/bin/bash
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set +x
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set -e
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. path.sh
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# 1. compile
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if [ ! -d ${SPEECHX_EXAMPLES} ]; then
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pushd ${SPEECHX_ROOT}
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bash build.sh
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popd
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fi
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# input
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mkdir -p data
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data=$PWD/data
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ckpt_dir=$data/model
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model_dir=$ckpt_dir/exp/deepspeech2_online/checkpoints/
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vocb_dir=$ckpt_dir/data/lang_char/
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# output
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aishell_wav_scp=aishell_test.scp
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if [ ! -d $data/test ]; then
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pushd $data
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wget -c https://paddlespeech.bj.bcebos.com/s2t/paddle_asr_online/aishell_test.zip
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unzip aishell_test.zip
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popd
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realpath $data/test/*/*.wav > $data/wavlist
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awk -F '/' '{ print $(NF) }' $data/wavlist | awk -F '.' '{ print $1 }' > $data/utt_id
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paste $data/utt_id $data/wavlist > $data/$aishell_wav_scp
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fi
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if [ ! -d $ckpt_dir ]; then
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mkdir -p $ckpt_dir
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wget -P $ckpt_dir -c https://paddlespeech.bj.bcebos.com/s2t/aishell/asr0/asr0_deepspeech2_online_aishell_ckpt_0.2.0.model.tar.gz
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tar xzfv $ckpt_dir/asr0_deepspeech2_online_aishell_ckpt_0.2.0.model.tar.gz -C $ckpt_dir
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fi
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export GLOG_logtostderr=1
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# 3. gen cmvn
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cmvn=$PWD/cmvn.ark
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cmvn-json2kaldi --json_file=$ckpt_dir/data/mean_std.json --cmvn_write_path=$cmvn
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text=$data/test/text
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graph_dir=./aishell_graph
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if [ ! -d $graph_dir ]; then
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wget -c https://paddlespeech.bj.bcebos.com/s2t/paddle_asr_online/aishell_graph.zip
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unzip aishell_graph.zip
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fi
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# 5. test websocket server
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websocket_server_main \
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--cmvn_file=$cmvn \
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--model_path=$model_dir/avg_1.jit.pdmodel \
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--streaming_chunk=0.1 \
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--convert2PCM32=true \
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--params_path=$model_dir/avg_1.jit.pdiparams \
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--word_symbol_table=$graph_dir/words.txt \
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--model_output_names=softmax_0.tmp_0,tmp_5,concat_0.tmp_0,concat_1.tmp_0 \
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--graph_path=$graph_dir/TLG.fst --max_active=7500 \
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--acoustic_scale=1.2
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@ -0,0 +1,85 @@
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// 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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#include "decoder/recognizer.h"
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#include "decoder/param.h"
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#include "kaldi/feat/wave-reader.h"
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#include "kaldi/util/table-types.h"
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DEFINE_string(wav_rspecifier, "", "test feature rspecifier");
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DEFINE_string(result_wspecifier, "", "test result wspecifier");
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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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ppspeech::RecognizerResource resource = ppspeech::InitRecognizerResoure();
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ppspeech::Recognizer recognizer(resource);
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kaldi::SequentialTableReader<kaldi::WaveHolder> wav_reader(
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FLAGS_wav_rspecifier);
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kaldi::TokenWriter result_writer(FLAGS_result_wspecifier);
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int sample_rate = 16000;
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float streaming_chunk = FLAGS_streaming_chunk;
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int chunk_sample_size = streaming_chunk * sample_rate;
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LOG(INFO) << "sr: " << sample_rate;
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LOG(INFO) << "chunk size (s): " << streaming_chunk;
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LOG(INFO) << "chunk size (sample): " << chunk_sample_size;
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int32 num_done = 0, num_err = 0;
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for (; !wav_reader.Done(); wav_reader.Next()) {
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std::string utt = wav_reader.Key();
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const kaldi::WaveData& wave_data = wav_reader.Value();
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int32 this_channel = 0;
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kaldi::SubVector<kaldi::BaseFloat> waveform(wave_data.Data(),
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this_channel);
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int tot_samples = waveform.Dim();
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LOG(INFO) << "wav len (sample): " << tot_samples;
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int sample_offset = 0;
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std::vector<kaldi::Vector<BaseFloat>> feats;
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int feature_rows = 0;
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while (sample_offset < tot_samples) {
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int cur_chunk_size =
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std::min(chunk_sample_size, tot_samples - sample_offset);
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kaldi::Vector<kaldi::BaseFloat> wav_chunk(cur_chunk_size);
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for (int i = 0; i < cur_chunk_size; ++i) {
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wav_chunk(i) = waveform(sample_offset + i);
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}
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recognizer.Accept(wav_chunk);
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if (cur_chunk_size < chunk_sample_size) {
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recognizer.SetFinished();
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}
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recognizer.Decode();
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sample_offset += cur_chunk_size;
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}
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std::string result;
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result = recognizer.GetFinalResult();
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recognizer.Reset();
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if (result.empty()) {
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// the TokenWriter can not write empty string.
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++num_err;
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KALDI_LOG << " the result of " << utt << " is empty";
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continue;
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}
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KALDI_LOG << " the result of " << utt << " is " << result;
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result_writer.Write(utt, result);
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++num_done;
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}
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}
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