From 32feb7d2be2dd1994401b613e95d1c3c1fd8a0e0 Mon Sep 17 00:00:00 2001
From: 嘉渊 <wangjiaming.wjm@alibaba-inc.com>
Date: 星期四, 27 四月 2023 17:10:31 +0800
Subject: [PATCH] update
---
egs/aishell/conformer/run.sh | 132 +++++++++++--------------------------------
1 files changed, 35 insertions(+), 97 deletions(-)
diff --git a/egs/aishell/conformer/run.sh b/egs/aishell/conformer/run.sh
index 16ebc67..05d35b7 100755
--- a/egs/aishell/conformer/run.sh
+++ b/egs/aishell/conformer/run.sh
@@ -3,37 +3,37 @@
. ./path.sh || exit 1;
# machines configuration
-CUDA_VISIBLE_DEVICES="0,1"
+CUDA_VISIBLE_DEVICES="2,3"
gpu_num=2
count=1
gpu_inference=true # Whether to perform gpu decoding, set false for cpu decoding
# for gpu decoding, inference_nj=ngpu*njob; for cpu decoding, inference_nj=njob
-njob=8
+njob=1
train_cmd=utils/run.pl
+infer_cmd=utils/run.pl
# general configuration
-feats_dir=".." #feature output dictionary, for large data
+feats_dir="../DATA" #feature output dictionary
exp_dir="."
lang=zh
dumpdir=dump/fbank
feats_type=fbank
token_type=char
-scp=feats.scp
-type=kaldi_ark
-stage=0
-stop_stage=4
+scp=wav.scp
+type=sound
+stage=3
+stop_stage=3
# feature configuration
feats_dim=80
-sample_frequency=16000
-nj=32
-speed_perturb="0.9,1.0,1.1"
+nj=64
# data
-data_aishell=
+raw_data=
+data_url=www.openslr.org/resources/33
# exp tag
-tag=""
+tag="exp1"
. utils/parse_options.sh || exit 1;
@@ -51,7 +51,7 @@
model_dir="baseline_$(basename "${asr_config}" .yaml)_${feats_type}_${lang}_${token_type}_${tag}"
inference_config=conf/decode_asr_transformer.yaml
-inference_asr_model=valid.acc.ave_10best.pth
+inference_asr_model=valid.acc.ave_10best.pb
# you can set gpu num for decoding here
gpuid_list=$CUDA_VISIBLE_DEVICES # set gpus for decoding, the same as training stage by default
@@ -59,14 +59,22 @@
if ${gpu_inference}; then
inference_nj=$[${ngpu}*${njob}]
+ _ngpu=1
else
inference_nj=$njob
+ _ngpu=0
+fi
+
+if [ ${stage} -le -1 ] && [ ${stop_stage} -ge -1 ]; then
+ echo "stage -1: Data Download"
+ local/download_and_untar.sh ${raw_data} ${data_url} data_aishell
+ local/download_and_untar.sh ${raw_data} ${data_url} resource_aishell
fi
if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
echo "stage 0: Data preparation"
# Data preparation
- local/aishell_data_prep.sh ${data_aishell}/data_aishell/wav ${data_aishell}/data_aishell/transcript ${feats_dir}
+ local/aishell_data_prep.sh ${raw_data}/data_aishell/wav ${raw_data}/data_aishell/transcript ${feats_dir}
for x in train dev test; do
cp ${feats_dir}/data/${x}/text ${feats_dir}/data/${x}/text.org
paste -d " " <(cut -f 1 -d" " ${feats_dir}/data/${x}/text.org) <(cut -f 2- -d" " ${feats_dir}/data/${x}/text.org | tr -d " ") \
@@ -76,42 +84,9 @@
done
fi
-feat_train_dir=${feats_dir}/${dumpdir}/train; mkdir -p ${feat_train_dir}
-feat_dev_dir=${feats_dir}/${dumpdir}/dev; mkdir -p ${feat_dev_dir}
-feat_test_dir=${feats_dir}/${dumpdir}/test; mkdir -p ${feat_test_dir}
if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
- echo "stage 1: Feature Generation"
- # compute fbank features
- fbankdir=${feats_dir}/fbank
- utils/compute_fbank.sh --cmd "$train_cmd" --nj $nj --speed_perturb ${speed_perturb} \
- ${feats_dir}/data/train ${exp_dir}/exp/make_fbank/train ${fbankdir}/train
- utils/fix_data_feat.sh ${fbankdir}/train
- utils/compute_fbank.sh --cmd "$train_cmd" --nj $nj \
- ${feats_dir}/data/dev ${exp_dir}/exp/make_fbank/dev ${fbankdir}/dev
- utils/fix_data_feat.sh ${fbankdir}/dev
- utils/compute_fbank.sh --cmd "$train_cmd" --nj $nj \
- ${feats_dir}/data/test ${exp_dir}/exp/make_fbank/test ${fbankdir}/test
- utils/fix_data_feat.sh ${fbankdir}/test
-
- # compute global cmvn
- utils/compute_cmvn.sh --cmd "$train_cmd" --nj $nj \
- ${fbankdir}/train ${exp_dir}/exp/make_fbank/train
-
- # apply cmvn
- utils/apply_cmvn.sh --cmd "$train_cmd" --nj $nj \
- ${fbankdir}/train ${fbankdir}/train/cmvn.json ${exp_dir}/exp/make_fbank/train ${feat_train_dir}
- utils/apply_cmvn.sh --cmd "$train_cmd" --nj $nj \
- ${fbankdir}/dev ${fbankdir}/train/cmvn.json ${exp_dir}/exp/make_fbank/dev ${feat_dev_dir}
- utils/apply_cmvn.sh --cmd "$train_cmd" --nj $nj \
- ${fbankdir}/test ${fbankdir}/train/cmvn.json ${exp_dir}/exp/make_fbank/test ${feat_test_dir}
-
- cp ${fbankdir}/train/text ${fbankdir}/train/speech_shape ${fbankdir}/train/text_shape ${feat_train_dir}
- cp ${fbankdir}/dev/text ${fbankdir}/dev/speech_shape ${fbankdir}/dev/text_shape ${feat_dev_dir}
- cp ${fbankdir}/test/text ${fbankdir}/test/speech_shape ${fbankdir}/test/text_shape ${feat_test_dir}
-
- utils/fix_data_feat.sh ${feat_train_dir}
- utils/fix_data_feat.sh ${feat_dev_dir}
- utils/fix_data_feat.sh ${feat_test_dir}
+ echo "stage 1: Feature and CMVN Generation"
+ utils/compute_cmvn.sh --cmd "$train_cmd" --nj $nj --feats_dim ${feats_dim} ${feats_dir}/data/${train_set}
fi
token_list=${feats_dir}/data/${lang}_token_list/char/tokens.txt
@@ -119,30 +94,23 @@
if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
echo "stage 2: Dictionary Preparation"
mkdir -p ${feats_dir}/data/${lang}_token_list/char/
-
+
echo "make a dictionary"
echo "<blank>" > ${token_list}
echo "<s>" >> ${token_list}
echo "</s>" >> ${token_list}
- utils/text2token.py -s 1 -n 1 --space "" ${feats_dir}/data/train/text | cut -f 2- -d" " | tr " " "\n" \
+ utils/text2token.py -s 1 -n 1 --space "" ${feats_dir}/data/$train_set/text | cut -f 2- -d" " | tr " " "\n" \
| sort | uniq | grep -a -v -e '^\s*$' | awk '{print $0}' >> ${token_list}
- num_token=$(cat ${token_list} | wc -l)
echo "<unk>" >> ${token_list}
- vocab_size=$(cat ${token_list} | wc -l)
- awk -v v=,${vocab_size} '{print $0v}' ${feat_train_dir}/text_shape > ${feat_train_dir}/text_shape.char
- awk -v v=,${vocab_size} '{print $0v}' ${feat_dev_dir}/text_shape > ${feat_dev_dir}/text_shape.char
- mkdir -p ${feats_dir}/asr_stats_fbank_zh_char/train
- mkdir -p ${feats_dir}/asr_stats_fbank_zh_char/dev
- cp ${feat_train_dir}/speech_shape ${feat_train_dir}/text_shape ${feat_train_dir}/text_shape.char ${feats_dir}/asr_stats_fbank_zh_char/train
- cp ${feat_dev_dir}/speech_shape ${feat_dev_dir}/text_shape ${feat_dev_dir}/text_shape.char ${feats_dir}/asr_stats_fbank_zh_char/dev
fi
# Training Stage
world_size=$gpu_num # run on one machine
if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
+ echo "stage 3: Training"
mkdir -p ${exp_dir}/exp/${model_dir}
mkdir -p ${exp_dir}/exp/${model_dir}/log
- INIT_FILE=$exp_dir/ddp_init
+ INIT_FILE=${exp_dir}/exp/${model_dir}/ddp_init
if [ -f $INIT_FILE ];then
rm -f $INIT_FILE
fi
@@ -153,26 +121,21 @@
rank=$i
local_rank=$i
gpu_id=$(echo $CUDA_VISIBLE_DEVICES | cut -d',' -f$[$i+1])
- asr_train.py \
+ train.py \
+ --task_name asr \
--gpu_id $gpu_id \
--use_preprocessor true \
--token_type char \
--token_list $token_list \
- --train_data_path_and_name_and_type ${feats_dir}/${dumpdir}/${train_set}/${scp},speech,${type} \
- --train_data_path_and_name_and_type ${feats_dir}/${dumpdir}/${train_set}/text,text,text \
- --train_shape_file ${feats_dir}/asr_stats_fbank_zh_char/${train_set}/speech_shape \
- --train_shape_file ${feats_dir}/asr_stats_fbank_zh_char/${train_set}/text_shape.char \
- --valid_data_path_and_name_and_type ${feats_dir}/${dumpdir}/${valid_set}/${scp},speech,${type} \
- --valid_data_path_and_name_and_type ${feats_dir}/${dumpdir}/${valid_set}/text,text,text \
- --valid_shape_file ${feats_dir}/asr_stats_fbank_zh_char/${valid_set}/speech_shape \
- --valid_shape_file ${feats_dir}/asr_stats_fbank_zh_char/${valid_set}/text_shape.char \
+ --data_dir ${feats_dir}/data \
+ --train_set ${train_set} \
+ --valid_set ${valid_set} \
+ --cmvn_file ${feats_dir}/data/${train_set}/cmvn/cmvn.mvn \
--resume true \
--output_dir ${exp_dir}/exp/${model_dir} \
--config $asr_config \
- --input_size $feats_dim \
--ngpu $gpu_num \
--num_worker_count $count \
- --multiprocessing_distributed true \
--dist_init_method $init_method \
--dist_world_size $world_size \
--dist_rank $rank \
@@ -180,29 +143,4 @@
} &
done
wait
-fi
-
-# Testing Stage
-if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then
- utils/easy_asr_infer.sh \
- --lang zh \
- --datadir ${feats_dir} \
- --feats_type ${feats_type} \
- --feats_dim ${feats_dim} \
- --token_type ${token_type} \
- --gpu_inference ${gpu_inference} \
- --inference_config "${inference_config}" \
- --test_sets "${test_sets}" \
- --token_list $token_list \
- --asr_exp ${exp_dir}/${model_dir} \
- --stage 12 \
- --stop_stage 12 \
- --scp $scp \
- --text text \
- --inference_nj $inference_nj \
- --njob $njob \
- --inference_asr_model $inference_asr_model \
- --gpuid_list $gpuid_list \
- --mode asr
-fi
-
+fi
\ No newline at end of file
--
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