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PaddleSpeech
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ds2 ol aishell egs

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pull/1707/head
Hui Zhang 3 years ago
parent c7b987c55d
commit 1e4207904e
6 changed files with 86 additions and 65 deletions
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22
speechx/examples/README.md
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@ -1,17 +1,25 @@
# Examples
# Examples for SpeechX
* dev - for speechx developer, using for test.
* ngram - using to build NGram ARPA lm.
* ds2_ol - ds2 streaming test under `aishell-1` test dataset.
The entrypoint is `ds2_ol/aishell/run.sh`
* glog - glog usage
* feat - mfcc, linear
* nnet - ds2 nn
* decoder - online decoder to work as offline
## How to run
`run.sh` is the entry point.
Example to play `decoder`:
Example to play `ds2_ol`:
```
pushd decoder
pushd ds2_ol/aishell
bash run.sh
```
## Display Model with [Netron](https://github.com/lutzroeder/netron)
```
pip install netron
netron exp/deepspeech2_online/checkpoints/avg_1.jit.pdmodel --port 8022 --host 10.21.55.20
```

2
speechx/examples/ds2_ol/aishell/.gitignore vendored
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@ -0,0 +1,2 @@
data
exp

2
speechx/examples/ds2_ol/aishell/path.sh
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@ -10,5 +10,5 @@ TOOLS_BIN=$SPEECHX_TOOLS/valgrind/install/bin
export LC_AL=C
SPEECHX_BIN=$SPEECHX_EXAMPLES/decoder:$SPEECHX_EXAMPLES/feat
SPEECHX_BIN=$SPEECHX_EXAMPLES/ds2_ol/decoder:$SPEECHX_EXAMPLES/ds2_ol/feat
export PATH=$PATH:$SPEECHX_BIN:$TOOLS_BIN

52
speechx/examples/ds2_ol/aishell/run.sh
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@ -4,6 +4,9 @@ set -e
. path.sh
nj=40
# 1. compile
if [ ! -d ${SPEECHX_EXAMPLES} ]; then
pushd ${SPEECHX_ROOT}
@ -19,52 +22,51 @@ ckpt_dir=$data/model
model_dir=$ckpt_dir/exp/deepspeech2_online/checkpoints/
vocb_dir=$ckpt_dir/data/lang_char/
lm=$data/zh_giga.no_cna_cmn.prune01244.klm
# output
mkdir -p exp
exp=$PWD/exp
aishell_wav_scp=aishell_test.scp
if [ ! -d $data/test ]; then
pushd $data
wget -c https://paddlespeech.bj.bcebos.com/s2t/paddle_asr_online/aishell_test.zip
unzip -d $data aishell_test.zip
unzip aishell_test.zip
popd
realpath $data/test/*/*.wav > $data/wavlist
awk -F '/' '{ print $(NF) }' $data/wavlist | awk -F '.' '{ print $1 }' > $data/utt_id
paste $data/utt_id $data/wavlist > $data/$aishell_wav_scp
fi
model_dir=$PWD/aishell_ds2_online_model
if [ ! -d $model_dir ]; then
mkdir -p $model_dir
wget -P $model_dir -c https://paddlespeech.bj.bcebos.com/s2t/aishell/asr0/asr0_deepspeech2_online_aishell_ckpt_0.2.0.model.tar.gz
tar xzfv $model_dir/asr0_deepspeech2_online_aishell_ckpt_0.2.0.model.tar.gz -C $model_dir
if [ ! -d $ckpt_dir ]; then
mkdir -p $ckpt_dir
wget -P $ckpt_dir -c https://paddlespeech.bj.bcebos.com/s2t/aishell/asr0/asr0_deepspeech2_online_aishell_ckpt_0.2.0.model.tar.gz
tar xzfv $model_dir/asr0_deepspeech2_online_aishell_ckpt_0.2.0.model.tar.gz -C $ckpt_dir
fi
lm=$data/zh_giga.no_cna_cmn.prune01244.klm
if [ ! -f $lm ]; then
pushd $data
wget -c https://deepspeech.bj.bcebos.com/zh_lm/zh_giga.no_cna_cmn.prune01244.klm
popd
fi
# 3. make feature
aishell_online_model=$model_dir/exp/deepspeech2_online/checkpoints
label_file=./aishell_result
wer=./aishell_wer
nj=40
export GLOG_logtostderr=1
#./local/split_data.sh $data $data/$aishell_wav_scp $aishell_wav_scp $nj
data=$PWD/data
# 3. gen linear feat
cmvn=$PWD/cmvn.ark
cmvn_json2binary_main --json_file=$model_dir/data/mean_std.json --cmvn_write_path=$cmvn
cmvn-json2kaldi --json_file=$ckpt_dir/data/mean_std.json --cmvn_write_path=$cmvn
./local/split_data.sh $data $data/$aishell_wav_scp $aishell_wav_scp $nj
utils/run.pl JOB=1:$nj $data/split${nj}/JOB/feat_log \
linear_spectrogram_without_db_norm_main \
linear-spectrogram-wo-db-norm-ol \
--wav_rspecifier=scp:$data/split${nj}/JOB/${aishell_wav_scp} \
--feature_wspecifier=ark,scp:$data/split${nj}/JOB/feat.ark,$data/split${nj}/JOB/feat.scp \
--cmvn_file=$cmvn \
@ -74,10 +76,10 @@ text=$data/test/text
# 4. recognizer
utils/run.pl JOB=1:$nj $data/split${nj}/JOB/log \
offline_decoder_sliding_chunk_main \
ctc-prefix-beam-search-decoder-ol \
--feature_rspecifier=scp:$data/split${nj}/JOB/feat.scp \
--model_path=$aishell_online_model/avg_1.jit.pdmodel \
--param_path=$aishell_online_model/avg_1.jit.pdiparams \
--model_path=$model_dir/avg_1.jit.pdmodel \
--param_path=$model_dir/avg_1.jit.pdiparams \
--model_output_names=softmax_0.tmp_0,tmp_5,concat_0.tmp_0,concat_1.tmp_0 \
--dict_file=$vocb_dir/vocab.txt \
--result_wspecifier=ark,t:$data/split${nj}/JOB/result
@ -87,10 +89,10 @@ utils/compute-wer.py --char=1 --v=1 ${label_file} $text > ${wer}
# 4. decode with lm
utils/run.pl JOB=1:$nj $data/split${nj}/JOB/log_lm \
offline_decoder_sliding_chunk_main \
ctc-prefix-beam-search-decoder-ol \
--feature_rspecifier=scp:$data/split${nj}/JOB/feat.scp \
--model_path=$aishell_online_model/avg_1.jit.pdmodel \
--param_path=$aishell_online_model/avg_1.jit.pdiparams \
--model_path=$model_dir/avg_1.jit.pdmodel \
--param_path=$model_dir/avg_1.jit.pdiparams \
--model_output_names=softmax_0.tmp_0,tmp_5,concat_0.tmp_0,concat_1.tmp_0 \
--dict_file=$vocb_dir/vocab.txt \
--lm_path=$lm \
@ -110,10 +112,10 @@ fi
# 5. test TLG decoder
utils/run.pl JOB=1:$nj $data/split${nj}/JOB/log_tlg \
offline_wfst_decoder_main \
wfst-decoder-ol \
--feature_rspecifier=scp:$data/split${nj}/JOB/feat.scp \
--model_path=$aishell_online_model/avg_1.jit.pdmodel \
--param_path=$aishell_online_model/avg_1.jit.pdiparams \
--model_path=$model_dir/avg_1.jit.pdmodel \
--param_path=$model_dir/avg_1.jit.pdiparams \
--word_symbol_table=$graph_dir/words.txt \
--model_output_names=softmax_0.tmp_0,tmp_5,concat_0.tmp_0,concat_1.tmp_0 \
--graph_path=$graph_dir/TLG.fst --max_active=7500 \

13
speechx/examples/ds2_ol/feat/cmvn-json2kaldi.cc
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@ -32,6 +32,8 @@ int main(int argc, char* argv[]) {
google::InitGoogleLogging(argv[0]);
LOG(INFO) << "cmvn josn path: " << FLAGS_json_file;
try {
padded_string json = padded_string::load(FLAGS_json_file);
ondemand::parser parser;
@ -44,7 +46,8 @@ int main(int argc, char* argv[]) {
mean_stat_vec.push_back(x);
}
// LOG(INFO) << mean_stat; this line will casue
// simdjson::simdjson_error("Objects and arrays can only be iterated when
// simdjson::simdjson_error("Objects and arrays can only be iterated
// when
// they are first encountered")
ondemand::array var_stat = val["var_stat"];
@ -65,8 +68,14 @@ int main(int argc, char* argv[]) {
cmvn_stats(0, mean_size) = frame_num;
LOG(INFO) << cmvn_stats;
kaldi::WriteKaldiObject(cmvn_stats, FLAGS_cmvn_write_path, FLAGS_binary);
kaldi::WriteKaldiObject(
cmvn_stats, FLAGS_cmvn_write_path, FLAGS_binary);
LOG(INFO) << "cmvn stats have write into: " << FLAGS_cmvn_write_path;
LOG(INFO) << "Binary: " << FLAGS_binary;
} catch (simdjson::simdjson_error& err) {
LOG(ERR) << err.what();
}
return 0;
}
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