#!/usr/bin/env bash export PYTHONPATH="" source /esat/spchtemp/scratch/jponcele/anaconda3/bin/activate espnet21 python --version # Set bash to 'debug' mode, it will exit on : # -e 'error', -u 'undefined variable', -o ... 'error in pipeline', -x 'print commands', set -e set -u set -o pipefail #################################################### stage=12 stop_stage=12 #################################################### # notes: geen speed perturbation, geen LM, geen word LM, geen NGRAM LM # EXP outdir=/esat/spchtemp/scratch/jponcele/espnet2 expdir=${outdir}/exp/exp-hpc st_tag=train_subtitling_chained_PL_C10_new_combined_nelf_all_dim512_iter10k st_stats_dir=/esat/spchtemp/scratch/jponcele/espnet2/exp/exp-st/st_stats_fbank_pitch_vl_joint_bpe5000_cgn_combined_tags_cased_punct_subs_train_all token_dir_suffix=cgn_combined_tags_cased_punct_subs_train_all nj=8 ngpu=0 # DATA st_train_set=st_train_all_combined_stochastic_cased_punct_speed_perturbed_cgn_subset st_valid_set=st_valid_nelf_12000h_combined_stochastic_cased_punct st_test_set="nbest-test" #aphasia_v2" #st_valid_nelf_12000h_combined_stochastic_cased_punct_subs_only dev_s subs_annot cgn_test_combined_resample_stochastic_tags_cased_punct st_valid_nelf_12000h_combined_stochastic_cased_punct_subs_only subs_annot dev_s cgn_test_combined_resample_stochastic_tags_cased_punct dev_s subs_annot" asr_train_set=train_s asr_valid_set=valid_s asr_test_set=dev_s subs_train_set=subs_train subs_valid_set=subs_valid subs_test_set=subs_test traincomps="a;b;c;d;f;g;h;i;j;k;l;m;n;o" decodecomps="b;f;g;h;i;j;k;l;m;n;o" local_data_opts="--repstr false --lowercase true --outdir data --traincomps ${traincomps} --decodecomps ${decodecomps}" subs_dir=/users/spraak/jponcele/vrt-scraper/vrtnew_subtitles_4feb local_subs_opts="--outdir data --subsdir ${subs_dir}" feats_type=fbank_pitch # LM use_word_lm=false # not yet supported! use_lm=false lm_config=conf/train_lm_transformer.yaml use_ngram=false # ST feats_normalize=utterance_mvn # recommended for pretrained models instead of globalmvn st_config=conf/tuning/train_subtitling_chained_C10_new_6layers_transformer_dim512.yaml inference_config=conf/st_decode_chained.yaml #_verbatim_only.yaml inference_nj=1 #8 #64 gpu_inference=true #false inference_st_model=averaged_model_30epochs.pth #valid.acc_asr.best.pth #averaged_model.pth #valid.acc_asr.ave.pth st_args="--batch_type custom_folded --valid_batch_type custom_folded" # "--input_size 0" # to use raw audio for w2v2 encoder ./subs.sh \ --stage ${stage} \ --stop_stage ${stop_stage} \ --ngpu ${ngpu} \ --nj ${nj} \ --gpu_inference false \ --dumpdir ${outdir}/dump \ --expdir ${expdir} \ --feats_type ${feats_type} \ --audio_format wav \ --min_wav_duration 0.1 \ --max_wav_duration 30 \ --token_joint true \ --src_token_type bpe \ --src_nbpe 5000 \ --src_bpemode unigram \ --src_case lc \ --tgt_token_type bpe \ --tgt_nbpe 5000 \ --tgt_bpemode unigram \ --tgt_case lc \ --oov "" \ --lang "vl" \ --src_lang "verbatim" \ --tgt_lang "subtitle" \ --local_subs_opts "${local_subs_opts}" \ --local_data_opts "${local_data_opts}" \ --use_lm ${use_lm} \ --use_word_lm ${use_word_lm} \ --lm_config ${lm_config} \ --use_ngram ${use_ngram} \ --st_config ${st_config} \ --st_args "${st_args}" \ --st_tag ${st_tag} \ --inference_config ${inference_config} \ --inference_nj ${inference_nj} \ --feats_normalize ${feats_normalize} \ --st_train_set "${st_train_set}" \ --st_valid_set "${st_valid_set}" \ --st_test_set "${st_test_set}" \ --asr_train_set ${asr_train_set} \ --asr_valid_set ${asr_valid_set} \ --asr_test_set ${asr_test_set} \ --subs_train_set ${subs_train_set} \ --subs_valid_set ${subs_valid_set} \ --subs_test_set ${subs_test_set} \ --st_stats_dir ${st_stats_dir} \ --inference_st_model ${inference_st_model} \ --token_dir_suffix ${token_dir_suffix} \ --gpu_inference ${gpu_inference} # --pretrained_asr ${pretrained_asr} \ #train_set=train_si284 #valid_set=test_dev93 #test_sets="test_dev93 test_eval92" # #./asr.sh \ # --lang "en" \ # --use_lm true \ # --token_type char \ # --nbpe 80 \ # --nlsyms_txt data/nlsyms.txt \ # --lm_config conf/train_lm_transformer.yaml \ # --asr_config conf/train_asr_transformer.yaml \ # --inference_config conf/decode.yaml \ # --train_set "${train_set}" \ # --valid_set "${valid_set}" \ # --test_sets "${test_sets}" \ # --bpe_train_text "data/train_si284/text" \ # --lm_train_text "data/train_si284/text data/local/other_text/text" "$@"