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56 lines
1.1 KiB
56 lines
1.1 KiB
7 years ago
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#! /usr/bin/env bash
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cd ../.. > /dev/null
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# download language model
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cd models/lm > /dev/null
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sh download_lm_en.sh
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if [ $? -ne 0 ]; then
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exit 1
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fi
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cd - > /dev/null
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# download well-trained model
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cd models/baidu_en8k > /dev/null
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sh download_model.sh
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if [ $? -ne 0 ]; then
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exit 1
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fi
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cd - > /dev/null
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# infer
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CUDA_VISIBLE_DEVICES=0 \
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python -u infer.py \
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--num_samples=10 \
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--trainer_count=1 \
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--beam_size=500 \
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--num_proc_bsearch=5 \
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--num_conv_layers=2 \
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--num_rnn_layers=3 \
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--rnn_layer_size=1024 \
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--alpha=1.4 \
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--beta=0.35 \
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--cutoff_prob=1.0 \
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--cutoff_top_n=40 \
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--use_gru=True \
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--use_gpu=True \
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--share_rnn_weights=False \
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--infer_manifest='data/librispeech/manifest.test-clean' \
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--mean_std_path='models/baidu_en8k/mean_std.npz' \
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--vocab_path='models/baidu_en8k/vocab.txt' \
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--model_path='models/baidu_en8k/params.tar.gz' \
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--lang_model_path='models/lm/common_crawl_00.prune01111.trie.klm' \
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--decoding_method='ctc_beam_search' \
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--error_rate_type='wer' \
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--specgram_type='linear'
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if [ $? -ne 0 ]; then
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echo "Failed in inference!"
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exit 1
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fi
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exit 0
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