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41 lines
1.2 KiB
41 lines
1.2 KiB
3 years ago
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#!/bin/bash
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set -e
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source path.sh
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stage=0
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stop_stage=100
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EXP_DIR=exp
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# LEXICON_NAME in {'phone', 'syllable', 'text'}
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LEXICON_NAME='phone'
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# get machine's cpu core number
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NUM_JOBS=`grep 'processor' /proc/cpuinfo | sort -u | wc -l`
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NUM_JOBS=$((NUM_JOBS/2))
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source ${MAIN_ROOT}/utils/parse_options.sh || exit 1;
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# download dataset、unzip and generate manifest
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if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
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# prepare data
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bash ./local/data.sh || exit -1
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fi
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# reorganize dataset for MFA
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if [ ! -d $EXP_DIR/thchs30_corpus ]; then
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echo "reorganizing thchs30 corpus..."
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python local/recorganize_thchs30.py --root-dir=./data --output-dir=$EXP_DIR/thchs30_corpus --script-type=$LEXICON_NAME
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echo "reorganization done."
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fi
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# MFA is in tools
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export PATH="${MAIN_ROOT}/tools/montreal-forced-aligner/bin"
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if [ ! -d "$EXP_DIR/thchs30_alignment" ]; then
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echo "Start MFA training..."
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mfa_train_and_align $EXP_DIR/thchs30_corpus "$EXP_DIR/$LEXICON_NAME.lexicon" $EXP_DIR/thchs30_alignment -o $EXP_DIR/thchs30_model --clean --verbose --temp_directory exp/.mfa_train_and_align --num_jobs $NUM_JOBS
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echo "training done! \nresults: $EXP_DIR/thchs30_alignment \nmodel: $EXP_DIR/thchs30_model\n"
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fi
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