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体验新版 GitCode,发现更多精彩内容 >>
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6b53ca7f
编写于
5月 05, 2022
作者:
Y
Yang Zhou
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差异文件
add fbank script
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speechx/examples/ds2_ol/aishell/run_fbank.sh
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speechx/examples/ds2_ol/aishell/run_fbank.sh
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6b53ca7f
#!/bin/bash
set
+x
set
-e
.
path.sh
nj
=
40
stage
=
0
stop_stage
=
5
.
utils/parse_options.sh
# 1. compile
if
[
!
-d
${
SPEECHX_EXAMPLES
}
]
;
then
pushd
${
SPEECHX_ROOT
}
bash build.sh
popd
fi
# input
mkdir
-p
data
data
=
$PWD
/data
ckpt_dir
=
$data
/fbank_model
model_dir
=
$ckpt_dir
/exp/deepspeech2_online/checkpoints/
vocb_dir
=
$ckpt_dir
/data/lang_char/
# output
mkdir
-p
exp
exp
=
$PWD
/exp
lm
=
$data
/zh_giga.no_cna_cmn.prune01244.klm
aishell_wav_scp
=
aishell_test.scp
if
[
${
stage
}
-le
0
]
&&
[
${
stop_stage
}
-ge
0
]
;
then
if
[
!
-d
$data
/test
]
;
then
pushd
$data
wget
-c
https://paddlespeech.bj.bcebos.com/s2t/paddle_asr_online/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
if
[
!
-f
$ckpt_dir
/data/mean_std.json
]
;
then
mkdir
-p
$ckpt_dir
pushd
$ckpt_dir
wget
-c
https://paddlespeech.bj.bcebos.com/s2t/wenetspeech/asr0/WIP1_asr0_deepspeech2_online_wenetspeech_ckpt_1.0.0a.model.tar.gz
tar
xzfv WIP1_asr0_deepspeech2_online_wenetspeech_ckpt_1.0.0a.model.tar.gz
popd
fi
if
[
!
-f
$lm
]
;
then
pushd
$data
wget
-c
https://deepspeech.bj.bcebos.com/zh_lm/zh_giga.no_cna_cmn.prune01244.klm
popd
fi
fi
# 3. make feature
text
=
$data
/test/text
label_file
=
./aishell_result_fbank
wer
=
./aishell_wer_fbank
export
GLOG_logtostderr
=
1
cmvn
=
$data
/cmvn_fbank.ark
if
[
${
stage
}
-le
1
]
&&
[
${
stop_stage
}
-ge
1
]
;
then
# 3. gen linear feat
cmvn-json2kaldi
--json_file
=
$ckpt_dir
/data/mean_std.json
--cmvn_write_path
=
$cmvn
--binary
=
false
./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
\
compute_fbank_main
\
--wav_rspecifier
=
scp:
$data
/split
${
nj
}
/JOB/
${
aishell_wav_scp
}
\
--feature_wspecifier
=
ark,scp:
$data
/split
${
nj
}
/JOB/fbank_feat.ark,
$data
/split
${
nj
}
/JOB/fbank_feat.scp
\
--cmvn_file
=
$cmvn
\
--streaming_chunk
=
36
fi
if
[
${
stage
}
-le
2
]
&&
[
${
stop_stage
}
-ge
2
]
;
then
# recognizer
utils/run.pl
JOB
=
1:
$nj
$data
/split
${
nj
}
/JOB/recog.fbank.wolm.log
\
ctc-prefix-beam-search-decoder-ol
\
--feature_rspecifier
=
scp:
$data
/split
${
nj
}
/JOB/fbank_feat.scp
\
--model_path
=
$model_dir
/avg_5.jit.pdmodel
\
--param_path
=
$model_dir
/avg_5.jit.pdiparams
\
--model_output_names
=
softmax_0.tmp_0,tmp_5,concat_0.tmp_0,concat_1.tmp_0
\
--model_cache_shapes
=
"5-1-2048,5-1-2048"
\
--dict_file
=
$vocb_dir
/vocab.txt
\
--result_wspecifier
=
ark,t:
$data
/split
${
nj
}
/JOB/result_fbank
cat
$data
/split
${
nj
}
/
*
/result_fbank
>
$exp
/
${
label_file
}
utils/compute-wer.py
--char
=
1
--v
=
1
$text
$exp
/
${
label_file
}
>
$exp
/
${
wer
}
fi
if
[
${
stage
}
-le
3
]
&&
[
${
stop_stage
}
-ge
3
]
;
then
# decode with lm
utils/run.pl
JOB
=
1:
$nj
$data
/split
${
nj
}
/JOB/recog.fbank.lm.log
\
ctc-prefix-beam-search-decoder-ol
\
--feature_rspecifier
=
scp:
$data
/split
${
nj
}
/JOB/fbank_feat.scp
\
--model_path
=
$model_dir
/avg_5.jit.pdmodel
\
--param_path
=
$model_dir
/avg_5.jit.pdiparams
\
--model_output_names
=
softmax_0.tmp_0,tmp_5,concat_0.tmp_0,concat_1.tmp_0
\
--model_cache_shapes
=
"5-1-2048,5-1-2048"
\
--dict_file
=
$vocb_dir
/vocab.txt
\
--lm_path
=
$lm
\
--result_wspecifier
=
ark,t:
$data
/split
${
nj
}
/JOB/fbank_result_lm
cat
$data
/split
${
nj
}
/
*
/fbank_result_lm
>
$exp
/
${
label_file
}
_lm
utils/compute-wer.py
--char
=
1
--v
=
1
$text
$exp
/
${
label_file
}
_lm
>
$exp
/
${
wer
}
.lm
fi
wfst
=
$data
/wfst_fbank/
if
[
${
stage
}
-le
4
]
&&
[
${
stop_stage
}
-ge
4
]
;
then
mkdir
-p
$wfst
if
[
!
-f
$wfst
/aishell_graph.zip
]
;
then
pushd
$wfst
wget
-c
https://paddlespeech.bj.bcebos.com/s2t/paddle_asr_online/aishell_graph2.zip
unzip aishell_graph2.zip
mv
aishell_graph2/
*
$wfst
popd
fi
fi
if
[
${
stage
}
-le
4
]
&&
[
${
stop_stage
}
-ge
4
]
;
then
# TLG decoder
utils/run.pl
JOB
=
1:
$nj
$data
/split
${
nj
}
/JOB/recog.fbank.wfst.log
\
wfst-decoder-ol
\
--feature_rspecifier
=
scp:
$data
/split
${
nj
}
/JOB/fbank_feat.scp
\
--model_path
=
$model_dir
/avg_5.jit.pdmodel
\
--param_path
=
$model_dir
/avg_5.jit.pdiparams
\
--word_symbol_table
=
$wfst
/words.txt
\
--model_output_names
=
softmax_0.tmp_0,tmp_5,concat_0.tmp_0,concat_1.tmp_0
\
--lm_path
=
$lm
\
--graph_path
=
$wfst
/TLG.fst
--max_active
=
7500
\
--acoustic_scale
=
1.2
\
--result_wspecifier
=
ark,t:
$data
/split
${
nj
}
/JOB/result_tlg
cat
$data
/split
${
nj
}
/
*
/result_tlg
>
$exp
/
${
label_file
}
_tlg
utils/compute-wer.py
--char
=
1
--v
=
1
$text
$exp
/
${
label_file
}
_tlg
>
$exp
/
${
wer
}
.tlg
echo
"wfst-decoder-ol have finished!!!"
echo
"please checkout in
${
exp
}
/
${
wer
}
.tlg"
fi
if
[
${
stage
}
-le
5
]
&&
[
${
stop_stage
}
-ge
5
]
;
then
utils/run.pl
JOB
=
1:
$nj
$data
/split
${
nj
}
/JOB/fbank_recognizer.log
\
recognizer_test_main
\
--wav_rspecifier
=
scp:
$data
/split
${
nj
}
/JOB/
${
aishell_wav_scp
}
\
--cmvn_file
=
$cmvn
\
--model_path
=
$model_dir
/avg_5.jit.pdmodel
\
--streaming_chunk
=
30
\
--use_fbank
=
true
\
--to_float32
=
false
\
--param_path
=
$model_dir
/avg_5.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
\
--model_cache_shapes
=
"5-1-2048,5-1-2048"
\
--graph_path
=
$graph_dir
/TLG.fst
--max_active
=
7500
\
--acoustic_scale
=
1.2
\
--result_wspecifier
=
ark,t:./result_fbank_recognizer
cat
$data
/split
${
nj
}
/
*
/result_recognizer
>
$exp
/
${
label_file
}
_recognizer
utils/compute-wer.py
--char
=
1
--v
=
1
$text
$exp
/
${
label_file
}
_recognizer
>
$exp
/
${
wer
}
.recognizer
echo
"recognizer test have finished!!!"
echo
"please checkout in
${
exp
}
/
${
wer
}
.recognizer"
fi
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