From 33d3d2084403fd34b79c835d2f2fe04f6cd8f738 Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期三, 13 九月 2023 09:33:54 +0800
Subject: [PATCH] Merge branch 'main' of github.com:alibaba-damo-academy/FunASR add

---
 egs/aishell/conformer/run.sh |  111 +++++++++++++++++++++++++++++++++++++++++++++++--------
 1 files changed, 95 insertions(+), 16 deletions(-)

diff --git a/egs/aishell/conformer/run.sh b/egs/aishell/conformer/run.sh
index 05d35b7..e8643e9 100755
--- a/egs/aishell/conformer/run.sh
+++ b/egs/aishell/conformer/run.sh
@@ -3,12 +3,12 @@
 . ./path.sh || exit 1;
 
 # machines configuration
-CUDA_VISIBLE_DEVICES="2,3"
+CUDA_VISIBLE_DEVICES="0,1"
 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=1
+njob=5
 train_cmd=utils/run.pl
 infer_cmd=utils/run.pl
 
@@ -16,20 +16,19 @@
 feats_dir="../DATA" #feature output dictionary
 exp_dir="."
 lang=zh
-dumpdir=dump/fbank
-feats_type=fbank
 token_type=char
-scp=wav.scp
 type=sound
-stage=3
-stop_stage=3
+scp=wav.scp
+speed_perturb="0.9 1.0 1.1"
+stage=0
+stop_stage=5
 
 # feature configuration
 feats_dim=80
 nj=64
 
 # data
-raw_data=
+raw_data=../raw_data
 data_url=www.openslr.org/resources/33
 
 # exp tag
@@ -48,7 +47,7 @@
 test_sets="dev test"
 
 asr_config=conf/train_asr_conformer.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.yaml
 inference_asr_model=valid.acc.ave_10best.pb
@@ -86,14 +85,14 @@
 
 if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
     echo "stage 1: Feature and CMVN Generation"
-    utils/compute_cmvn.sh --cmd "$train_cmd" --nj $nj --feats_dim ${feats_dim} ${feats_dir}/data/${train_set}
+    utils/compute_cmvn.sh --fbankdir ${feats_dir}/data/${train_set} --cmd "$train_cmd" --nj $nj --feats_dim ${feats_dim} --config_file "$asr_config" --scale 1.0
 fi
 
-token_list=${feats_dir}/data/${lang}_token_list/char/tokens.txt
+token_list=${feats_dir}/data/${lang}_token_list/$token_type/tokens.txt
 echo "dictionary: ${token_list}"
 if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
     echo "stage 2: Dictionary Preparation"
-    mkdir -p ${feats_dir}/data/${lang}_token_list/char/
+    mkdir -p ${feats_dir}/data/${lang}_token_list/$token_type/
 
     echo "make a dictionary"
     echo "<blank>" > ${token_list}
@@ -104,10 +103,16 @@
     echo "<unk>" >> ${token_list}
 fi
 
-# Training Stage
+# LM Training Stage
 world_size=$gpu_num  # run on one machine
 if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
-    echo "stage 3: Training"
+    echo "stage 3: LM Training"
+fi
+
+# ASR Training Stage
+world_size=$gpu_num  # run on one machine
+if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then
+    echo "stage 4: ASR 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
@@ -125,12 +130,14 @@
                 --task_name asr \
                 --gpu_id $gpu_id \
                 --use_preprocessor true \
-                --token_type char \
+                --token_type $token_type \
                 --token_list $token_list \
                 --data_dir ${feats_dir}/data \
                 --train_set ${train_set} \
                 --valid_set ${valid_set} \
-                --cmvn_file ${feats_dir}/data/${train_set}/cmvn/cmvn.mvn \
+                --data_file_names "wav.scp,text" \
+                --cmvn_file ${feats_dir}/data/${train_set}/cmvn/am.mvn \
+                --speed_perturb ${speed_perturb} \
                 --resume true \
                 --output_dir ${exp_dir}/exp/${model_dir} \
                 --config $asr_config \
@@ -143,4 +150,76 @@
         } &
         done
         wait
+fi
+
+# Testing Stage
+if [ ${stage} -le 5 ] && [ ${stop_stage} -ge 5 ]; then
+    echo "stage 5: 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}/data/${dset}"
+        key_file=${_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}" \
+                --cmvn_file ${feats_dir}/data/${train_set}/cmvn/am.mvn \
+                --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 asr \
+                ${_opts}
+
+        for f in token token_int score text; do
+            if [ -f "${_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
+
+# Prepare files for ModelScope fine-tuning and inference
+if [ ${stage} -le 6 ] && [ ${stop_stage} -ge 6 ]; then
+    echo "stage 6: ModelScope Preparation"
+    cp ${feats_dir}/data/${train_set}/cmvn/am.mvn ${exp_dir}/exp/${model_dir}/am.mvn
+    vocab_size=$(cat ${token_list} | wc -l)
+    python utils/gen_modelscope_configuration.py \
+        --am_model_name $inference_asr_model \
+        --mode asr \
+        --model_name conformer \
+        --dataset aishell \
+        --output_dir $exp_dir/exp/$model_dir \
+        --vocab_size $vocab_size \
+        --tag $tag
 fi
\ No newline at end of file

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