mirror of
https://github.com/k2-fsa/icefall.git
synced 2025-08-08 09:32:20 +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
119 lines
3.7 KiB
Bash
Executable File
119 lines
3.7 KiB
Bash
Executable File
#!/usr/bin/env bash
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# fix segmentation fault reported in https://github.com/k2-fsa/icefall/issues/674
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export PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python
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set -eou pipefail
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stage=-1
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stop_stage=100
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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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# - $dl_dir/aidatatang_200zh
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# You can find "corpus" and "transcript" inside it.
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# You can download it at
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# https://openslr.org/62/
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dl_dir=$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/aidatatang_200zh/transcript/aidatatang_200_zh_transcript.txt ]; then
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lhotse download aidatatang-200zh $dl_dir
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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 aidatatang_200zh manifest"
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# We assume that you have downloaded the aidatatang_200zh corpus
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# to $dl_dir/aidatatang_200zh
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if [ ! -f data/manifests/aidatatang_200zh/.manifests.done ]; then
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mkdir -p data/manifests/aidatatang_200zh
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lhotse prepare aidatatang-200zh $dl_dir data/manifests/aidatatang_200zh
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touch data/manifests/aidatatang_200zh/.manifests.done
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fi
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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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if [ ! -f data/manifests/.manifests.done ]; then
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log "It may take 6 minutes"
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mkdir -p data/manifests/
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lhotse prepare musan $dl_dir/musan data/manifests/
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touch data/manifests/.manifests.done
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fi
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fi
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if [ $stage -le 3 ] && [ $stop_stage -ge 3 ]; then
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log "Stage 3: Compute fbank for musan"
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if [ ! -f data/fbank/.msuan.done ]; then
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mkdir -p data/fbank
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./local/compute_fbank_musan.py
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touch data/fbank/.msuan.done
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fi
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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 aidatatang_200zh"
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if [ ! -f data/fbank/.aidatatang_200zh.done ]; then
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mkdir -p data/fbank
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./local/compute_fbank_aidatatang_200zh.py --perturb-speed True
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touch data/fbank/.aidatatang_200zh.done
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fi
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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: 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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# 1. wget -O jq https://github.com/stedolan/jq/releases/download/jq-1.6/jq-linux64
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# 2. chmod +x ./jq
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# 3. cp jq /usr/bin
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if [ ! -f $lang_char_dir/text ]; then
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gunzip -c data/manifests/aidatatang_200zh/aidatatang_supervisions_train.jsonl.gz \
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|jq '.text' |sed -e 's/["text:\t ]*//g' | sed 's/"//g' \
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| ./local/text2token.py -t "char" > $lang_char_dir/text
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fi
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# Prepare words.txt
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if [ ! -f $lang_char_dir/text_words ]; then
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gunzip -c data/manifests/aidatatang_200zh/aidatatang_supervisions_train.jsonl.gz \
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| jq '.text' | sed -e 's/["text:\t]*//g' | sed 's/"//g' \
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| ./local/text2token.py -t "char" > $lang_char_dir/text_words
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fi
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cat $lang_char_dir/text_words | sed 's/ /\n/g' | sort -u | sed '/^$/d' \
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| uniq > $lang_char_dir/words_no_ids.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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