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egs/yomdle_zh/v1/run.sh
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#!/bin/bash set -e stage=0 nj=60 database_slam=/export/corpora5/slam/SLAM/Chinese/transcribed database_yomdle=/export/corpora5/slam/YOMDLE/final_chinese download_dir=data_yomdle_chinese/download/ extra_lm=download/extra_lm.txt data_dir=data_yomdle_chinese exp_dir=exp_yomdle_chinese . ./cmd.sh . ./path.sh . ./utils/parse_options.sh if [ $stage -le -1 ]; then local/create_download.sh --database-slam $database_slam \ --database-yomdle $database_yomdle \ --slam-dir download/slam_chinese \ --yomdle-dir download/yomdle_chinese fi if [ $stage -le 0 ]; then mkdir -p data_slam_chinese/slam mkdir -p data_yomdle_chinese/yomdle local/process_data.py download/slam_chinese data_slam_chinese/slam local/process_data.py download/yomdle_chinese data_yomdle_chinese/yomdle ln -s ../data_slam_chinese/slam ${data_dir}/test ln -s ../data_yomdle_chinese/yomdle ${data_dir}/train image/fix_data_dir.sh ${data_dir}/test image/fix_data_dir.sh ${data_dir}/train fi mkdir -p $data_dir/{train,test}/data if [ $stage -le 1 ]; then echo "$0: Obtaining image groups. calling get_image2num_frames" echo "Date: $(date)." image/get_image2num_frames.py --feat-dim 60 $data_dir/train image/get_allowed_lengths.py --frame-subsampling-factor 4 10 $data_dir/train for datasplit in train test; do echo "$0: Extracting features and calling compute_cmvn_stats for dataset: $datasplit. " echo "Date: $(date)." local/extract_features.sh --nj $nj --cmd "$cmd" \ --feat-dim 60 --num-channels 3 \ $data_dir/${datasplit} steps/compute_cmvn_stats.sh $data_dir/${datasplit} || exit 1; done echo "$0: Fixing data directory for train dataset" echo "Date: $(date)." utils/fix_data_dir.sh $data_dir/train fi if [ $stage -le 2 ]; then for datasplit in train; do echo "$(date) stage 2: Performing augmentation, it will double training data" local/augment_data.sh --nj $nj --cmd "$cmd" --feat-dim 60 $data_dir/${datasplit} $data_dir/${datasplit}_aug $data_dir steps/compute_cmvn_stats.sh $data_dir/${datasplit}_aug || exit 1; done fi if [ $stage -le 3 ]; then echo "$0: Preparing dictionary and lang..." if [ ! -f $data_dir/train/bpe.out ]; then cut -d' ' -f2- $data_dir/train/text | utils/lang/bpe/prepend_words.py | python3 utils/lang/bpe/learn_bpe.py -s 700 > $data_dir/train/bpe.out for datasplit in test train train_aug; do cut -d' ' -f1 $data_dir/$datasplit/text > $data_dir/$datasplit/ids cut -d' ' -f2- $data_dir/$datasplit/text | utils/lang/bpe/prepend_words.py | python3 utils/lang/bpe/apply_bpe.py -c $data_dir/train/bpe.out | sed 's/@@//g' > $data_dir/$datasplit/bpe_text mv $data_dir/$datasplit/text $data_dir/$datasplit/text.old paste -d' ' $data_dir/$datasplit/ids $data_dir/$datasplit/bpe_text > $data_dir/$datasplit/text done fi local/prepare_dict.sh --data-dir $data_dir --dir $data_dir/local/dict # This recipe uses byte-pair encoding, the silences are part of the words' pronunciations. # So we set --sil-prob to 0.0 utils/prepare_lang.sh --num-sil-states 4 --num-nonsil-states 8 --sil-prob 0.0 --position-dependent-phones false \ $data_dir/local/dict "<sil>" $data_dir/lang/temp $data_dir/lang utils/lang/bpe/add_final_optional_silence.sh --final-sil-prob 0.5 $data_dir/lang fi if [ $stage -le 4 ]; then echo "$0: Estimating a language model for decoding..." local/train_lm.sh --data-dir $data_dir --dir $data_dir/local/local_lm utils/format_lm.sh $data_dir/lang $data_dir/local/local_lm/data/arpa/3gram_unpruned.arpa.gz \ $data_dir/local/dict/lexicon.txt $data_dir/lang_test fi if [ $stage -le 5 ]; then echo "$0: Calling the flat-start chain recipe..." echo "Date: $(date)." local/chain/run_flatstart_cnn1a.sh --nj $nj --train-set train_aug --data-dir $data_dir --exp-dir $exp_dir fi if [ $stage -le 6 ]; then echo "$0: Aligning the training data using the e2e chain model..." echo "Date: $(date)." steps/nnet3/align.sh --nj $nj --cmd "$cmd" --use-gpu false \ --scale-opts '--transition-scale=1.0 --acoustic-scale=1.0 --self-loop-scale=1.0' \ $data_dir/train_aug $data_dir/lang $exp_dir/chain/e2e_cnn_1a $exp_dir/chain/e2e_ali_train fi if [ $stage -le 7 ]; then echo "$0: Building a tree and training a regular chain model using the e2e alignments..." echo "Date: $(date)." local/chain/run_cnn_e2eali_1b.sh --nj $nj --train-set train_aug --data-dir $data_dir --exp-dir $exp_dir fi if [ $stage -le 8 ]; then echo "$0: Estimating a language model for lattice rescoring...$(date)" local/train_lm_lr.sh --data-dir $data_dir --dir $data_dir/local/local_lm_lr --extra-lm $extra_lm --order 6 utils/build_const_arpa_lm.sh $data_dir/local/local_lm_lr/data/arpa/6gram_unpruned.arpa.gz \ $data_dir/lang_test $data_dir/lang_test_lr steps/lmrescore_const_arpa.sh $data_dir/lang_test $data_dir/lang_test_lr \ $data_dir/test $exp_dir/chain/cnn_e2eali_1b/decode_test $exp_dir/chain/cnn_e2eali_1b/decode_test_lr fi |