mirror of
https://github.com/k2-fsa/icefall.git
synced 2025-08-09 10:02:22 +00:00
50 lines
1.7 KiB
Bash
Executable File
50 lines
1.7 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=0
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stop_stage=0
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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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if [ $stage -le 0 ] && [ $stop_stage -ge 0 ]; then
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log "stage 0: Download whisper-large-v2 aishell 1 fbank feature from huggingface"
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# pip install huggingface_hub['cli']
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# for aishell 1
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huggingface-cli download --repo-type dataset --local-dir data yuekai/aishell_whisper_fbank_lhotse
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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: Download whisper-large-v2 multi-hans-zh fbank feature from huggingface"
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# for multi-hans-zh
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huggingface-cli download --repo-type dataset --local-dir data/fbank yuekai/wenetspeech_whisper_fbank_lhotse
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huggingface-cli download --repo-type dataset --local-dir data/fbank yuekai/multi_hans_zh_whisper_fbank_lhotse
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huggingface-cli download --repo-type dataset --local-dir data/fbank yuekai/alimeeting_aishell4_training_whisper_fbank_lhotse
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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: Download whisper-large-v2 speechio test sets fbank feature from huggingface"
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# for speechio test sets
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mkdir data_speechio
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huggingface-cli download --repo-type model --local-dir data_speechio yuekai/icefall_asr_speechio
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mv data_speechio/fbank/* data/fbank
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fi
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