From 688fb902dd625981060b00788ed70c4c155d2b50 Mon Sep 17 00:00:00 2001
From: 嘉渊 <wangjiaming.wjm@alibaba-inc.com>
Date: 星期一, 15 五月 2023 10:59:59 +0800
Subject: [PATCH] update repo
---
funasr/utils/prepare_data.py | 5 ++
egs/aishell/paraformerbert/run.sh | 103 +++++++++++++--------------------------------------
funasr/bin/train.py | 6 +++
egs/aishell/paraformerbert/local/extract_embeds.sh | 4 -
4 files changed, 39 insertions(+), 79 deletions(-)
diff --git a/egs/aishell/paraformerbert/local/extract_embeds.sh b/egs/aishell/paraformerbert/local/extract_embeds.sh
index 9cf5940..453efb8 100755
--- a/egs/aishell/paraformerbert/local/extract_embeds.sh
+++ b/egs/aishell/paraformerbert/local/extract_embeds.sh
@@ -5,8 +5,6 @@
bert_model_root="../../huggingface_models"
bert_model_name="bert-base-chinese"
-#bert_model_name="chinese-roberta-wwm-ext"
-#bert_model_name="mengzi-bert-base"
raw_dataset_path="../DATA"
model_path=${bert_model_root}/${bert_model_name}
@@ -16,7 +14,7 @@
for data_set in train dev test;do
scp=$raw_dataset_path/dump/fbank/${data_set}/text
- local_scp_dir_raw=$raw_dataset_path/embeds/$bert_model_name/${data_set}
+ local_scp_dir_raw=${raw_dataset_path}/${data_set}
local_scp_dir=$local_scp_dir_raw/split$nj
local_records_dir=$local_scp_dir_raw/ark
diff --git a/egs/aishell/paraformerbert/run.sh b/egs/aishell/paraformerbert/run.sh
index bcbe1eb..f4ffaf7 100755
--- a/egs/aishell/paraformerbert/run.sh
+++ b/egs/aishell/paraformerbert/run.sh
@@ -16,12 +16,11 @@
feats_dir="../DATA" #feature output dictionary, for large data
exp_dir="."
lang=zh
-dumpdir=dump/fbank
-feats_type=fbank
token_type=char
-scp=feats.scp
-type=kaldi_ark
-stage=0
+type=sound
+scp=wav.scp
+speed_perturb="0.9 1.0 1.1"
+stage=3
stop_stage=4
skip_extract_embed=false
@@ -30,15 +29,14 @@
# 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;
@@ -53,7 +51,7 @@
test_sets="dev test"
asr_config=conf/train_asr_paraformerbert_conformer_12e_6d_2048_256.yaml
-model_dir="baseline_$(basename "${asr_config}" .yaml)_${feats_type}_${lang}_${token_type}_${tag}"
+model_dir="baseline_$(basename "${asr_config}" .yaml)_${lang}_${token_type}_${tag}"
inference_config=conf/decode_asr_transformer_noctc_1best.yaml
inference_asr_model=valid.acc.ave_10best.pb
@@ -70,10 +68,17 @@
_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 " ") \
@@ -83,46 +88,9 @@
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 --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 --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 --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 --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_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 ${feat_test_dir}
-
- #generate ark list
- utils/gen_ark_list.sh --cmd "$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 ${feat_dev_dir}
+ echo "stage 1: Feature and CMVN Generation"
+ utils/compute_cmvn.sh --cmd "$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
@@ -135,17 +103,9 @@
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 ${feats_dir}/asr_stats_fbank_zh_char/dev
fi
# Training Stage
@@ -172,31 +132,22 @@
rank=$i
local_rank=$i
gpu_id=$(echo $CUDA_VISIBLE_DEVICES | cut -d',' -f$[$i+1])
- asr_train_paraformer.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_data_path_and_name_and_type ${feats_dir}/embeds/${bert_model_name}/${train_set}/embeds.scp,embed,${type} \
- --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 \
- --train_shape_file ${feats_dir}/embeds/${bert_model_name}/${train_set}/embeds.shape \
- --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_data_path_and_name_and_type ${feats_dir}/embeds/${bert_model_name}/${valid_set}/embeds.scp,embed,${type} \
- --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 \
- --valid_shape_file ${feats_dir}/embeds/${bert_model_name}/${valid_set}/embeds.shape \
+ --data_dir ${feats_dir}/data \
+ --train_set ${train_set} \
+ --valid_set ${valid_set} \
+ --cmvn_file ${feats_dir}/data/${train_set}/cmvn/cmvn.mvn \
+ --speed_perturb ${speed_perturb} \
--resume true \
--output_dir ${exp_dir}/exp/${model_dir} \
--config $asr_config \
- --allow_variable_data_keys true \
- --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 \
diff --git a/funasr/bin/train.py b/funasr/bin/train.py
index ba5df1d..53e5bde 100755
--- a/funasr/bin/train.py
+++ b/funasr/bin/train.py
@@ -347,6 +347,12 @@
default=True,
help="Apply preprocessing to data or not",
)
+ parser.add_argument(
+ "--embed_path",
+ type=str,
+ default=None,
+ help="for model which requires embeds",
+ )
# optimization related
parser.add_argument(
diff --git a/funasr/utils/prepare_data.py b/funasr/utils/prepare_data.py
index 24382c7..d11eece 100644
--- a/funasr/utils/prepare_data.py
+++ b/funasr/utils/prepare_data.py
@@ -181,6 +181,11 @@
["{}/{}/wav.scp".format(args.data_dir, args.valid_set), data_names[0], data_types[0]],
["{}/{}/text".format(args.data_dir, args.valid_set), data_names[1], data_types[1]]
]
+ if args.embed_path is not None:
+ args.train_data_path_and_name_and_type[0].append(
+ "{}/embed/kaldi_ark".format(os.path.join(args.embed_path, args.train_set, "embeds.scp")))
+ args.valid_data_path_and_name_and_type[0].append(
+ "{}/embed/kaldi_ark".format(os.path.join(args.embed_path, args.dev_set, "embeds.scp")))
else:
args.train_data_file = os.path.join(args.data_dir, args.train_set, "data.list")
args.valid_data_file = os.path.join(args.data_dir, args.valid_set, "data.list")
--
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