| egs/aishell/conformer/run.sh | ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史 | |
| egs/aishell/data2vec_paraformer_finetune/run.sh | ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史 | |
| egs/aishell/data2vec_transformer_finetune/run.sh | ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史 | |
| egs/aishell/paraformer/run.sh | ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史 | |
| egs/aishell/paraformerbert/run.sh | ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史 | |
| egs/aishell/transformer/run.sh | ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史 | |
| egs/librispeech/conformer/run.sh | ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史 | |
| egs/librispeech_100h/conformer/run.sh | ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史 |
egs/aishell/conformer/run.sh
@@ -20,8 +20,8 @@ type=sound scp=wav.scp speed_perturb="0.9 1.0 1.1" stage=3 stop_stage=4 stage=0 stop_stage=5 # feature configuration feats_dim=80 @@ -103,10 +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 @@ -146,8 +152,8 @@ fi # Testing Stage if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then echo "stage 4: Inference" 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)" egs/aishell/data2vec_paraformer_finetune/run.sh
@@ -20,8 +20,8 @@ type=sound scp=wav.scp speed_perturb="0.9 1.0 1.1" stage=3 stop_stage=4 stage=0 stop_stage=5 # feature configuration feats_dim=80 @@ -106,11 +106,17 @@ 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" python utils/download_model.py --model_name ${model_name} # download pretrained model on ModelScope echo "stage 3: LM Training" fi # Training Stage world_size=$gpu_num # run on one machine if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then echo "stage 4: ASR Training" python utils/download_model.py --model_name ${model_name} # download pretrained model on ModelScope mkdir -p ${exp_dir}/exp/${model_dir} mkdir -p ${exp_dir}/exp/${model_dir}/log INIT_FILE=${exp_dir}/exp/${model_dir}/ddp_init @@ -150,8 +156,8 @@ fi # Testing Stage if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then echo "stage 4: Inference" 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)" egs/aishell/data2vec_transformer_finetune/run.sh
@@ -20,8 +20,8 @@ type=sound scp=wav.scp speed_perturb="0.9 1.0 1.1" stage=3 stop_stage=4 stage=0 stop_stage=5 # feature configuration feats_dim=80 @@ -106,11 +106,17 @@ 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" python utils/download_model.py --model_name ${model_name} # download pretrained model on ModelScope echo "stage 3: LM Training" fi # Training Stage world_size=$gpu_num # run on one machine if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then echo "stage 4: ASR Training" python utils/download_model.py --model_name ${model_name} # download pretrained model on ModelScope mkdir -p ${exp_dir}/exp/${model_dir} mkdir -p ${exp_dir}/exp/${model_dir}/log INIT_FILE=${exp_dir}/exp/${model_dir}/ddp_init @@ -151,8 +157,8 @@ fi # Testing Stage if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then echo "stage 4: Inference" 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)" egs/aishell/paraformer/run.sh
@@ -20,8 +20,8 @@ type=sound scp=wav.scp speed_perturb="0.9 1.0 1.1" stage=3 stop_stage=4 stage=0 stop_stage=5 # feature configuration feats_dim=80 @@ -103,10 +103,16 @@ echo "<unk>" >> ${token_list} fi # Training Stage # LM Training Stage world_size=$gpu_num # run on one machine if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then echo "stage 3: Training" echo "stage 3: LM Training" fi # Training Stage world_size=$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 @@ -146,8 +152,8 @@ fi # Testing Stage if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then echo "stage 4: Inference" 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)" egs/aishell/paraformerbert/run.sh
@@ -20,8 +20,8 @@ type=sound scp=wav.scp speed_perturb="0.9 1.0 1.1" stage=3 stop_stage=4 stage=0 stop_stage=5 skip_extract_embed=false bert_model_name="bert-base-chinese" @@ -107,10 +107,16 @@ echo "<unk>" >> ${token_list} fi # Training Stage # LM Training Stage world_size=$gpu_num # run on one machine if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then echo "stage 3: Training" echo "stage 3: LM Training" fi # Training Stage world_size=$gpu_num # run on one machine if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then echo "stage 4: ASR Training" if ! "${skip_extract_embed}"; then echo "extract embeddings..." local/extract_embeds.sh \ @@ -158,8 +164,8 @@ fi # Testing Stage if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then echo "stage 4: Inference" 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 "${inference_config}" .yaml)" @@ -170,7 +176,7 @@ exit 0 fi mkdir -p "${_logdir}" _data="${feats_dir}/${dumpdir}/${dset}" _data="${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") @@ -191,6 +197,7 @@ --njob ${njob} \ --gpuid_list ${gpuid_list} \ --data_path_and_name_and_type "${_data}/${scp},speech,${type}" \ --cmvn_file ${feats_dir}/data/${train_set}/cmvn/cmvn.mvn \ --key_file "${_logdir}"/keys.JOB.scp \ --asr_train_config "${asr_exp}"/config.yaml \ --asr_model_file "${asr_exp}"/"${inference_asr_model}" \ egs/aishell/transformer/run.sh
@@ -20,8 +20,8 @@ type=sound scp=wav.scp speed_perturb="0.9 1.0 1.1" stage=3 stop_stage=4 stage=0 stop_stage=5 # feature configuration feats_dim=80 @@ -103,10 +103,16 @@ echo "<unk>" >> ${token_list} fi # Training Stage # LM Training Stage world_size=$gpu_num # run on one machine if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then echo "stage 3: Training" echo "stage 3: LM Training" fi # Training Stage world_size=$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 @@ -146,8 +152,8 @@ fi # Testing Stage if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then echo "stage 4: Inference" 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)" egs/librispeech/conformer/run.sh
@@ -21,7 +21,7 @@ scp=wav.scp speed_perturb="0.9 1.0 1.1" stage=0 stop_stage=2 stop_stage=5 # feature configuration feats_dim=80 @@ -116,10 +116,16 @@ 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 @@ -162,8 +168,8 @@ fi # Testing Stage if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then echo "stage 4: Inference" 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)" egs/librispeech_100h/conformer/run.sh
@@ -20,8 +20,8 @@ type=sound scp=wav.scp speed_perturb="0.9 1.0 1.1" stage=3 stop_stage=4 stage=0 stop_stage=5 # feature configuration feats_dim=80 @@ -111,10 +111,16 @@ 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 @@ -157,8 +163,8 @@ fi # Testing Stage if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then echo "stage 4: Inference" 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)"
