From f9fed09e96f43e7eab88378fc444c4987933badb Mon Sep 17 00:00:00 2001
From: zhifu gao <zhifu.gzf@alibaba-inc.com>
Date: 星期五, 09 十二月 2022 23:57:51 +0800
Subject: [PATCH] Merge pull request #10 from alibaba-damo-academy/dev
---
egs/aishell/paraformerbert/run.sh | 142 ++++++++++++++++++++++++++++++-----------------
1 files changed, 90 insertions(+), 52 deletions(-)
diff --git a/egs/aishell/paraformerbert/run.sh b/egs/aishell/paraformerbert/run.sh
index 15d659c..6f331ec 100755
--- a/egs/aishell/paraformerbert/run.sh
+++ b/egs/aishell/paraformerbert/run.sh
@@ -10,9 +10,11 @@
# for gpu decoding, inference_nj=ngpu*njob; for cpu decoding, inference_nj=njob
njob=8
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, for large data
+exp_dir="."
lang=zh
dumpdir=dump/fbank
feats_type=fbank
@@ -51,11 +53,9 @@
test_sets="dev test"
asr_config=conf/train_asr_paraformerbert_conformer_12e_6d_2048_256.yaml
-run_dir="exp"
model_dir="baseline_$(basename "${asr_config}" .yaml)_${feats_type}_${lang}_${token_type}_${tag}"
-exp_dir=$run_dir/$model_dir
-inference_config=conf/decode_asr_transformer.yaml
+inference_config=conf/decode_asr_transformer_noctc_1best.yaml
inference_asr_model=valid.acc.ave_10best.pth
# you can set gpu num for decoding here
@@ -64,20 +64,22 @@
if ${gpu_inference}; then
inference_nj=$[${ngpu}*${njob}]
+ _ngpu=1
else
inference_nj=$njob
+ _ngpu=0
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
+ local/aishell_data_prep.sh ${data_aishell}/data_aishell/wav ${data_aishell}/data_aishell/transcript ${feats_dir}
for x in train dev test; do
- cp data/${x}/text data/${x}/text.org
- paste -d " " <(cut -f 1 -d" " data/${x}/text.org) <(cut -f 2- -d" " data/${x}/text.org | tr -d " ") \
- > data/${x}/text
- utils/text2token.py -n 1 -s 1 data/${x}/text > data/${x}/text.org
- mv data/${x}/text.org data/${x}/text
+ 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 " ") \
+ > ${feats_dir}/data/${x}/text
+ utils/text2token.py -n 1 -s 1 ${feats_dir}/data/${x}/text > ${feats_dir}/data/${x}/text.org
+ mv ${feats_dir}/data/${x}/text.org ${feats_dir}/data/${x}/text
done
fi
@@ -88,27 +90,27 @@
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} \
- data/train exp/make_fbank/train ${fbankdir}/train
+ utils/compute_fbank.sh --cmd "$train_cmd" --nj $nj --feats_dim ${feats_dim} --sample_frequency ${sample_frequency} --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 \
- data/dev exp/make_fbank/dev ${fbankdir}/dev
+ utils/compute_fbank.sh --cmd "$train_cmd" --nj $nj --feats_dim ${feats_dim} --sample_frequency ${sample_frequency} \
+ ${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 \
- data/test exp/make_fbank/test ${fbankdir}/test
+ utils/compute_fbank.sh --cmd "$train_cmd" --nj $nj --feats_dim ${feats_dim} --sample_frequency ${sample_frequency} \
+ ${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 \
- ${fbankdir}/train exp/make_fbank/train
+ utils/compute_cmvn.sh --cmd "$train_cmd" --nj $nj --feats_dim ${feats_dim} \
+ ${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/make_fbank/train ${feat_train_dir}
+ ${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/make_fbank/dev ${feat_dev_dir}
+ ${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/make_fbank/test ${feat_test_dir}
+ ${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}
@@ -117,29 +119,33 @@
utils/fix_data_feat.sh ${feat_train_dir}
utils/fix_data_feat.sh ${feat_dev_dir}
utils/fix_data_feat.sh ${feat_test_dir}
+
+ #generate ark list
+ utils/gen_ark_list.sh --cmd "$train_cmd" --nj $nj ${feat_train_dir} ${fbankdir}/train ${feat_train_dir}
+ utils/gen_ark_list.sh --cmd "$train_cmd" --nj $nj ${feat_dev_dir} ${fbankdir}/dev ${feat_dev_dir}
fi
token_list=${feats_dir}/data/${lang}_token_list/char/tokens.txt
echo "dictionary: ${token_list}"
if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
echo "stage 2: Dictionary Preparation"
- mkdir -p data/${lang}_token_list/char/
+ 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 "" data/train/text | cut -f 2- -d" " | tr " " "\n" \
+ utils/text2token.py -s 1 -n 1 --space "" ${feats_dir}/data/train/text | cut -f 2- -d" " | tr " " "\n" \
| sort | uniq | grep -a -v -e '^\s*$' | 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 asr_stats_fbank_zh_char/train
- mkdir -p asr_stats_fbank_zh_char/dev
- cp ${feat_train_dir}/speech_shape ${feat_train_dir}/text_shape ${feat_train_dir}/text_shape.char asr_stats_fbank_zh_char/train
- cp ${feat_dev_dir}/speech_shape ${feat_dev_dir}/text_shape ${feat_dev_dir}/text_shape.char asr_stats_fbank_zh_char/dev
+ 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 ${feats_dir}/asr_stats_fbank_zh_char/dev
fi
if ! "${skip_extract_embed}"; then
@@ -152,9 +158,10 @@
# Training Stage
world_size=$gpu_num # run on one machine
if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
- mkdir -p $exp_dir
- mkdir -p $exp_dir/log
- INIT_FILE=$exp_dir/ddp_init
+ echo "stage 3: Training"
+ mkdir -p ${exp_dir}/exp/${model_dir}
+ mkdir -p ${exp_dir}/exp/${model_dir}/log
+ INIT_FILE=${exp_dir}/exp/${model_dir}/ddp_init
if [ -f $INIT_FILE ];then
rm -f $INIT_FILE
fi
@@ -183,7 +190,7 @@
--valid_shape_file ${feats_dir}/asr_stats_fbank_zh_char/${valid_set}/text_shape.char \
--valid_shape_file ${feats_dir}/embeds/${bert_model_name}/${valid_set}/embeds.shape \
--resume true \
- --output_dir $exp_dir \
+ --output_dir ${exp_dir}/exp/${model_dir} \
--config $asr_config \
--input_size $feats_dim \
--ngpu $gpu_num \
@@ -201,26 +208,57 @@
# 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 \
- --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 \
- --gpu_inference ${gpu_inference} \
- --mode paraformer
+ echo "stage 4: Inference"
+ for dset in ${test_sets}; do
+ asr_exp=${exp_dir}/exp/${model_dir}
+ inference_tag="$(basename "${inference_config}" .yaml)"
+ _dir="${asr_exp}/${inference_tag}/${inference_asr_model}/${dset}"
+ _logdir="${_dir}/logdir"
+ if [ -d ${_dir} ]; then
+ echo "${_dir} is already exists. if you want to decode again, please delete this dir first."
+ exit 0
+ fi
+ mkdir -p "${_logdir}"
+ _data="${feats_dir}/${dumpdir}/${dset}"
+ key_file=${_data}/${scp}
+ num_scp_file="$(<${key_file} wc -l)"
+ _nj=$([ $inference_nj -le $num_scp_file ] && echo "$inference_nj" || echo "$num_scp_file")
+ split_scps=
+ for n in $(seq "${_nj}"); do
+ split_scps+=" ${_logdir}/keys.${n}.scp"
+ done
+ # shellcheck disable=SC2086
+ utils/split_scp.pl "${key_file}" ${split_scps}
+ _opts=
+ if [ -n "${inference_config}" ]; then
+ _opts+="--config ${inference_config} "
+ fi
+ ${infer_cmd} --gpu "${_ngpu}" --max-jobs-run "${_nj}" JOB=1:"${_nj}" "${_logdir}"/asr_inference.JOB.log \
+ python -m funasr.bin.asr_inference_launch \
+ --batch_size 1 \
+ --ngpu "${_ngpu}" \
+ --njob ${njob} \
+ --gpuid_list ${gpuid_list} \
+ --data_path_and_name_and_type "${_data}/${scp},speech,${type}" \
+ --key_file "${_logdir}"/keys.JOB.scp \
+ --asr_train_config "${asr_exp}"/config.yaml \
+ --asr_model_file "${asr_exp}"/"${inference_asr_model}" \
+ --output_dir "${_logdir}"/output.JOB \
+ --mode paraformer \
+ ${_opts}
+
+ for f in token token_int score text; do
+ if [ -f "${_logdir}/output.1/1best_recog/${f}" ]; then
+ for i in $(seq "${_nj}"); do
+ cat "${_logdir}/output.${i}/1best_recog/${f}"
+ done | sort -k1 >"${_dir}/${f}"
+ fi
+ done
+ python utils/proce_text.py ${_dir}/text ${_dir}/text.proc
+ python utils/proce_text.py ${_data}/text ${_data}/text.proc
+ python utils/compute_wer.py ${_data}/text.proc ${_dir}/text.proc ${_dir}/text.cer
+ tail -n 3 ${_dir}/text.cer > ${_dir}/text.cer.txt
+ cat ${_dir}/text.cer.txt
+ done
fi
--
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