mirror of
https://github.com/k2-fsa/icefall.git
synced 2025-08-09 18:12:19 +00:00
120 lines
4.1 KiB
Bash
Executable File
120 lines
4.1 KiB
Bash
Executable File
#!/usr/bin/env bash
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# Prepare script for MLS English ASR recipe in icefall
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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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# Configuration for BPE tokenizer
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vocab_sizes=(2000) # You can add more sizes like (500 1000 2000) for comparison
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# Directory where dataset will be downloaded
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dl_dir=$PWD/download
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. shared/parse_options.sh || exit 1
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# All files generated by this script are saved in "data".
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mkdir -p data
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mkdir -p data/audio
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mkdir -p data/manifests
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mkdir -p data/lang
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log() {
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local fname=${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 "Starting MLS English data preparation"
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if [ $stage -le 0 ] && [ $stop_stage -ge 0 ]; then
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log "Stage 0: Download MLS English dataset"
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# Check if huggingface_hub is installed
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if ! python -c "import huggingface_hub" &> /dev/null; then
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log "huggingface_hub Python library not found. Installing it now..."
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# Using --break-system-packages for Debian/Ubuntu environments where pip install might fail without it
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python -m pip install huggingface_hub || \
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python -m pip install huggingface_hub --break-system-packages || { \
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log "Failed to install huggingface_hub. Please install it manually: pip install huggingface_hub"; \
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exit 1; \
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}
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log "huggingface_hub installed successfully."
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fi
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# Check if the dataset already exists to avoid re-downloading
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if [ ! -d "$dl_dir/mls_english" ]; then
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log "Dataset not found at $dl_dir/mls_english. Starting download..."
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if ! python ./local/utils/download_mls_english.py --dl-dir "$dl_dir"; then
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log "Failed to download MLS English dataset via download_mls_english.py"
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exit 1
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fi
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else
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log "Dataset already exists at $dl_dir/mls_english. Skipping download."
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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 MLS English manifest"
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# # We assume that you have downloaded the MLS English corpus
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# # to $dl_dir/mls_english
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# if [ ! -e data/manifests/.mls_english.done ]; then
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# # lhotse prepare mls_english -j $nj $dl_dir/mls_english data/manifests
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# python local/utils/save_audios.py --num-jobs 8 --dataset-dir $dl_dir/mls_english --audio-dir ./data/audio --manifest-dir ./data/manifests
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# touch data/manifests/.mls_english.done
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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: Compute MLS English fbank"
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if [ ! -e data/manifests/.mls_english-validated.done ]; then
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python local/compute_fbank_mls_english.py \
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--manifest-dir data/manifests \
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--audio-dir data/audio \
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--dl-dir $dl_dir/mls_english
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# --dl-dir /root/datasets/parler-tts--mls_eng
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python local/validate_manifest.py --manifest data/manifests/mls_eng_cuts_train.jsonl.gz
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python local/validate_manifest.py --manifest data/manifests/mls_eng_cuts_dev.jsonl.gz
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python local/validate_manifest.py --manifest data/manifests/mls_eng_cuts_test.jsonl.gz
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touch data/manifests/.mls_english-validated.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 transcript for BPE training"
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if [ ! -f data/lang/transcript.txt ]; then
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log "Generating transcripts for BPE training"
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python local/utils/generate_transcript.py \
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--dataset-path $dl_dir/mls_english \
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--lang-dir data/lang \
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--split train
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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: Prepare BPE tokenizer"
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for vocab_size in ${vocab_sizes[@]}; do
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log "Training BPE model with vocab_size=${vocab_size}"
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bpe_dir=data/lang/bpe_${vocab_size}
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mkdir -p $bpe_dir
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if [ ! -f $bpe_dir/bpe.model ]; then
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python local/train_bpe_model.py \
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--lang-dir $bpe_dir \
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--vocab-size $vocab_size \
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--transcript data/lang/transcript.txt
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fi
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done
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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: Show manifest statistics"
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python local/display_manifest_statistics.py --manifest-dir data/manifests > data/manifests/manifest_statistics.txt
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cat data/manifests/manifest_statistics.txt
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fi
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log "MLS English data preparation completed successfully"
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