mirror of
https://github.com/k2-fsa/icefall.git
synced 2025-08-09 18:12:19 +00:00
74806b744b
* disable speed perturbation by default
* minor fixes
* minor updates
* updated bash scripts to incorporate with the `speed-perturb` arg
* minor fixes
1. changed the naming scheme from `speed-perturb` to `perturb-speed` to align with the librispeech recipe
>> 00256a7669/egs/librispeech/ASR/local/compute_fbank_librispeech.py (L65)
2. changed arg type for `perturb-speed` to str2bool
126 lines
3.7 KiB
Bash
Executable File
126 lines
3.7 KiB
Bash
Executable File
#!/usr/bin/env bash
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set -eou pipefail
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stage=-1
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stop_stage=100
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use_gss=true # Use GSS-based enhancement with MDM setting
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# We assume dl_dir (download dir) contains the following
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# directories and files. If not, they will be downloaded
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# by this script automatically.
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#
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# - $dl_dir/alimeeting
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# This directory contains the following files downloaded from
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# https://openslr.org/62/
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#
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# - Train_Ali_far.tar.gz
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# - Train_Ali_near.tar.gz
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# - Test_Ali.tar.gz
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# - Eval_Ali.tar.gz
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#
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# - $dl_dir/musan
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# This directory contains the following directories downloaded from
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# http://www.openslr.org/17/
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#
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# - music
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# - noise
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# - speech
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dl_dir=$PWD/download
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. shared/parse_options.sh || exit 1
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# All files generated by this script are saved in "data".
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# You can safely remove "data" and rerun this script to regenerate it.
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mkdir -p data
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log() {
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# This function is from espnet
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local fname=${BASH_SOURCE[1]##*/}
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echo -e "$(date '+%Y-%m-%d %H:%M:%S') (${fname}:${BASH_LINENO[0]}:${FUNCNAME[1]}) $*"
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}
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log "dl_dir: $dl_dir"
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if [ $stage -le 0 ] && [ $stop_stage -ge 0 ]; then
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log "Stage 0: Download data"
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if [ ! -f $dl_dir/alimeeting/Train_Ali_far.tar.gz ]; then
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lhotse download ali-meeting $dl_dir/alimeeting
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fi
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fi
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if [ $stage -le 1 ] && [ $stop_stage -ge 1 ]; then
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log "Stage 1: Prepare alimeeting manifest"
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# We assume that you have downloaded the alimeeting corpus
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# to $dl_dir/alimeeting
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for part in ihm sdm mdm; do
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mkdir -p data/manifests/alimeeting
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lhotse prepare ali-meeting --mic $part --save-mono --normalize-text m2met \
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$dl_dir/alimeeting data/manifests
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done
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fi
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if [ $stage -le 2 ] && [ $stop_stage -ge 2 ]; then
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log "Stage 2: Prepare musan manifest"
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# We assume that you have downloaded the musan corpus
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# to data/musan
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mkdir -p data/manifests
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lhotse prepare musan $dl_dir/musan data/manifests
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fi
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if [ $stage -le 3 ] && [ $stop_stage -ge 3 ] && [ $use_gss = true ]; then
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log "Stage 3: Apply GSS enhancement on MDM data (this stage requires a GPU)"
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# We assume that you have installed the GSS package: https://github.com/desh2608/gss
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local/prepare_alimeeting_gss.sh data/manifests exp/alimeeting_gss
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fi
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if [ $stage -le 4 ] && [ $stop_stage -ge 4 ]; then
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log "Stage 4: Compute fbank for musan"
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mkdir -p data/fbank
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python local/compute_fbank_musan.py
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fi
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if [ $stage -le 5 ] && [ $stop_stage -ge 5 ]; then
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log "Stage 5: Compute fbank for alimeeting"
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mkdir -p data/fbank
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python local/compute_fbank_alimeeting.py --perturb-speed True
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log "Combine features from train splits"
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lhotse combine data/manifests/cuts_train_{ihm,ihm_rvb,sdm,gss}.jsonl.gz - | shuf |\
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gzip -c > data/manifests/cuts_train_all.jsonl.gz
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fi
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if [ $stage -le 6 ] && [ $stop_stage -ge 6 ]; then
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log "Stage 6: Prepare char based lang"
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lang_char_dir=data/lang_char
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mkdir -p $lang_char_dir
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# Prepare text.
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# Note: in Linux, you can install jq with the following command:
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# wget -O jq https://github.com/stedolan/jq/releases/download/jq-1.6/jq-linux64
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gunzip -c data/manifests/alimeeting-sdm_supervisions_train.jsonl.gz \
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| jq ".text" | sed 's/"//g' \
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| ./local/text2token.py -t "char" > $lang_char_dir/text
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# Prepare words segments
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python ./local/text2segments.py \
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--input $lang_char_dir/text \
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--output $lang_char_dir/text_words_segmentation
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cat $lang_char_dir/text_words_segmentation | sed "s/ /\n/g" \
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| sort -u | sed "/^$/d" \
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| uniq > $lang_char_dir/words_no_ids.txt
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# Prepare words.txt
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if [ ! -f $lang_char_dir/words.txt ]; then
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./local/prepare_words.py \
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--input-file $lang_char_dir/words_no_ids.txt \
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--output-file $lang_char_dir/words.txt
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fi
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if [ ! -f $lang_char_dir/L_disambig.pt ]; then
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./local/prepare_char.py
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fi
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fi
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