| | |
|---|
| | | 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=8 |
|---|
| | | njob=1 |
|---|
| | | train_cmd=utils/run.pl |
|---|
| | | infer_cmd=utils/run.pl |
|---|
| | | |
|---|
| | | # general configuration |
|---|
| | | feats_dir="../DATA" #feature output dictionary, for large data |
|---|
| | | feats_dir="../DATA" #feature output dictionary |
|---|
| | | exp_dir="." |
|---|
| | | lang=zh |
|---|
| | | dumpdir=dump/fbank |
|---|
| | |
|---|
| | | model_dir="baseline_$(basename "${asr_config}" .yaml)_${feats_type}_${lang}_${token_type}_${tag}" |
|---|
| | | |
|---|
| | | inference_config=conf/decode_asr_transformer_noctc_1best.yaml |
|---|
| | | inference_asr_model=valid.acc.ave_10best.pth |
|---|
| | | inference_asr_model=valid.acc.ave_10best.pb |
|---|
| | | |
|---|
| | | # you can set gpu num for decoding here |
|---|
| | | gpuid_list=$CUDA_VISIBLE_DEVICES # set gpus for decoding, the same as training stage by default |
|---|
| | |
|---|
| | | tail -n 3 ${_dir}/text.cer > ${_dir}/text.cer.txt |
|---|
| | | cat ${_dir}/text.cer.txt |
|---|
| | | done |
|---|
| | | fi |
|---|
| | | |
|---|
| | | fi |
|---|
