speech_recognition/FunASR
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嘉渊 2023-05-11 11:57:04 +08:00
parent 2793afe461
commit 73ad5651a4
1 changed files with 6 additions and 58 deletions
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64
egs/librispeech_100h/conformer/run.sh
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@ -19,15 +19,15 @@ lang=en
token_type=bpe
type=sound
scp=wav.scp
stage=0
stop_stage=0
stage=1
stop_stage=1
# feature configuration
feats_dim=80
nj=64
# data
raw_data=/nfs/wangjiaming.wjm/librispeech
raw_data=
data_url=www.openslr.org/resources/12
# bpe model
@ -45,7 +45,7 @@ set -e
set -u
set -o pipefail
train_set=train_960
train_set=train_clean_100
valid_set=dev
test_sets="test_clean test_other dev_clean dev_other"
@ -84,61 +84,9 @@ if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
done
fi
feat_train_dir=${feats_dir}/${dumpdir}/$train_set; mkdir -p ${feat_train_dir}
feat_dev_clean_dir=${feats_dir}/${dumpdir}/dev_clean; mkdir -p ${feat_dev_clean_dir}
feat_dev_other_dir=${feats_dir}/${dumpdir}/dev_other; mkdir -p ${feat_dev_other_dir}
feat_test_clean_dir=${feats_dir}/${dumpdir}/test_clean; mkdir -p ${feat_test_clean_dir}
feat_test_other_dir=${feats_dir}/${dumpdir}/test_other; mkdir -p ${feat_test_other_dir}
feat_dev_dir=${feats_dir}/${dumpdir}/$valid_set; mkdir -p ${feat_dev_dir}
if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
echo "stage 1: Feature Generation"
# compute fbank features
fbankdir=${feats_dir}/fbank
for x in dev_clean dev_other test_clean test_other; do
utils/compute_fbank.sh --cmd "$train_cmd" --nj 1 --max_lengths 3000 --feats_dim ${feats_dim} --sample_frequency ${sample_frequency} \
${feats_dir}/data/${x} ${exp_dir}/exp/make_fbank/${x} ${fbankdir}/${x}
utils/fix_data_feat.sh ${fbankdir}/${x}
done
mkdir ${feats_dir}/data/$train_set
train_sets="train_clean_100 train_clean_360 train_other_500"
for file in wav.scp text; do
( for f in $train_sets; do cat $feats_dir/data/$f/$file; done ) | sort -k1 > $feats_dir/data/$train_set/$file || exit 1;
done
utils/compute_fbank.sh --cmd "$train_cmd" --nj $nj --max_lengths 3000 --feats_dim ${feats_dim} --sample_frequency ${sample_frequency} --speed_perturb ${speed_perturb} \
${feats_dir}/data/$train_set ${exp_dir}/exp/make_fbank/$train_set ${fbankdir}/$train_set
utils/fix_data_feat.sh ${fbankdir}/$train_set
# compute global cmvn
utils/compute_cmvn.sh --cmd "$train_cmd" --nj $nj --feats_dim ${feats_dim} \
${fbankdir}/$train_set ${exp_dir}/exp/make_fbank/$train_set
# apply cmvn
utils/apply_cmvn.sh --cmd "$train_cmd" --nj $nj \
${fbankdir}/$train_set ${fbankdir}/$train_set/cmvn.json ${exp_dir}/exp/make_fbank/$train_set ${feat_train_dir}
utils/apply_cmvn.sh --cmd "$train_cmd" --nj 1 \
${fbankdir}/dev_clean ${fbankdir}/$train_set/cmvn.json ${exp_dir}/exp/make_fbank/dev_clean ${feat_dev_clean_dir}
utils/apply_cmvn.sh --cmd "$train_cmd" --nj 1\
${fbankdir}/dev_other ${fbankdir}/$train_set/cmvn.json ${exp_dir}/exp/make_fbank/dev_other ${feat_dev_other_dir}
utils/apply_cmvn.sh --cmd "$train_cmd" --nj 1 \
${fbankdir}/test_clean ${fbankdir}/$train_set/cmvn.json ${exp_dir}/exp/make_fbank/test_clean ${feat_test_clean_dir}
utils/apply_cmvn.sh --cmd "$train_cmd" --nj 1 \
${fbankdir}/test_other ${fbankdir}/$train_set/cmvn.json ${exp_dir}/exp/make_fbank/test_other ${feat_test_other_dir}
cp ${fbankdir}/$train_set/text ${fbankdir}/$train_set/speech_shape ${fbankdir}/$train_set/text_shape ${feat_train_dir}
cp ${fbankdir}/dev_clean/text ${fbankdir}/dev_clean/speech_shape ${fbankdir}/dev_clean/text_shape ${feat_dev_clean_dir}
cp ${fbankdir}/dev_other/text ${fbankdir}/dev_other/speech_shape ${fbankdir}/dev_other/text_shape ${feat_dev_other_dir}
cp ${fbankdir}/test_clean/text ${fbankdir}/test_clean/speech_shape ${fbankdir}/test_clean/text_shape ${feat_test_clean_dir}
cp ${fbankdir}/test_other/text ${fbankdir}/test_other/speech_shape ${fbankdir}/test_other/text_shape ${feat_test_other_dir}
dev_sets="dev_clean dev_other"
for file in feats.scp text speech_shape text_shape; do
( for f in $dev_sets; do cat $feats_dir/${dumpdir}/$f/$file; done ) | sort -k1 > $feat_dev_dir/$file || exit 1;
done
#generate ark list
utils/gen_ark_list.sh --cmd "$train_cmd" --nj $nj ${feat_train_dir} ${fbankdir}/${train_set} ${feat_train_dir}
utils/gen_ark_list.sh --cmd "$train_cmd" --nj $nj ${feat_dev_dir} ${fbankdir}/${valid_set} ${feat_dev_dir}
echo "stage 1: Feature and CMVN Generation"
utils/compute_cmvn.sh --cmd "$train_cmd" --nj $nj --feats_dim ${feats_dim} ${feats_dir}/data/${train_set}
fi
dict=${feats_dir}/data/lang_char/${train_set}_${bpemode}${nbpe}_units.txt