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add rnnlm recipe for librispeech #2830

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Nov 19, 2018
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add rnnlm recipe for librispeech #2830

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952aa93
add rnnlm recipe for librispeech
Nov 12, 2018
7c8db7f
add RNNLM rescoring results for librispeech
Nov 19, 2018
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add RNNLM rescoring results for librispeech
  • Loading branch information
Ke Li committed Nov 19, 2018
commit 7c8db7f40052d85ee11939883e4b89179753c06b
56 changes: 38 additions & 18 deletions egs/librispeech/s5/local/rnnlm/tuning/run_tdnn_lstm_1a.sh
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Expand Up @@ -10,6 +10,25 @@
# Train objf: -5.74 -5.51 -5.38 -5.29 -5.22 -5.16 -5.12 -5.08 -5.05 -5.02 -4.99 -4.97 -4.97 -4.93 -4.90 -4.87 -4.84 -4.82 -4.79 -4.77 -4.75 -4.73 -4.71 -4.69 -4.67
# Dev objf: -6.00 -5.61 -5.45 -5.36 -5.29 -5.24 -5.20 -5.18 -5.16 -5.13 -5.12 -5.11 -5.11 -5.09 -5.07 -5.06 -5.05 -5.04 -5.03 -5.03 -5.03 -5.03 -5.03 -5.03 -5.03 -5.03

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Can you please include some WER comparisons?

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sure, I have WER numbers on an old chain model. I'm running a new one now. will update the rescoring results on that in a few days.

# WER summary on dev and test sets
# System tdnn_1d_sp +lattice_rescore +nbest_rescore
# WER on dev(fglarge) 3.34 2.97 2.98
# WER on dev(tglarge) 3.44 3.02 3.07
# WER on dev_other(fglarge) 8.70 7.98 8.00
# WER on dev_other(tglarge) 9.25 8.28 8.35
# WER on test(fglarge) 3.77 3.41 3.40
# WER on test(tglarge) 3.85 3.50 3.47
# WER on test_other(fglarge) 8.91 8.22 8.21
# WER on test_other(tglarge) 9.31 8.55 8.49

# command to get the WERs above:
# tdnn_1d_sp
# for test in dev_clean test_clean dev_other test_other; do for lm in fglarge tglarge; do grep WER exp/chain_cleaned/tdnn_1d_sp/decode_${test}_${lm}/wer* | best_wer.sh; done; done
# tdnn_1d_sp with lattice rescoring
# for test in dev_clean test_clean dev_other test_other; do for lm in fglarge tglarge; do grep WER exp/chain_cleaned/tdnn_1d_sp/decode_${test}_${lm}_rnnlm_1a_rescore/wer* | best_wer.sh; done; done
# tdnn_1d_sp with nbest rescoring
# for test in dev_clean test_clean dev_other test_other; do for lm in fglarge tglarge; do grep WER exp/chain_cleaned/tdnn_1d_sp/decode_${test}_${lm}_rnnlm_1a_nbest_rescore/wer* | best_wer.sh; done; done

# Begin configuration section.

dir=exp/rnnlm_lstm_1a
Expand Down Expand Up @@ -106,7 +125,6 @@ if [ $stage -le 3 ]; then
--cmd "$train_cmd" $dir
fi

LM=fglarge
if [ $stage -le 4 ] && $run_lat_rescore; then
echo "$0: Perform lattice-rescoring on $ac_model_dir"
# LM=tgsmall # if using the original 3-gram G.fst as old lm
Expand All @@ -115,29 +133,31 @@ if [ $stage -le 4 ] && $run_lat_rescore; then
pruned=_pruned
fi
for decode_set in test_clean test_other dev_clean dev_other; do
decode_dir=${ac_model_dir}/decode_${decode_set}_${LM}

# Lattice rescoring
rnnlm/lmrescore$pruned.sh \
--cmd "$decode_cmd --mem 8G" \
--weight 0.4 --max-ngram-order $ngram_order \
data/lang_test_$LM $dir \
data/${decode_set}_hires ${decode_dir} \
exp/decode_${decode_set}_${LM}_${decode_dir_suffix}_rescore
for LM in fglarge tglarge; do
decode_dir=${ac_model_dir}/decode_${decode_set}_${LM}
# Lattice rescoring
rnnlm/lmrescore$pruned.sh \
--cmd "$decode_cmd --mem 8G" \
--weight 0.45 --max-ngram-order $ngram_order \
data/lang_test_$LM $dir \
data/${decode_set}_hires ${decode_dir} \
exp/chain_cleaned/tdnn_1d_sp/decode_${decode_set}_${LM}_${decode_dir_suffix}_rescore
done
done
fi

if [ $stage -le 5 ] && $run_nbest_rescore; then
echo "$0: Perform nbest-rescoring on $ac_model_dir"
for decode_set in test_clean test_other dev_clean dev_other; do
decode_dir=${ac_model_dir}/decode_${decode_set}_${LM}

# Nbest rescoring
rnnlm/lmrescore_nbest.sh \
--cmd "$decode_cmd --mem 8G" --N 20 \
0.4 data/lang_test_$LM $dir \
data/${decode_set}_hires ${decode_dir} \
exp/decode_${decode_set}_${LM}_${decode_dir_suffix}_nbest_rescore
for LM in fglarge tglarge; do
decode_dir=${ac_model_dir}/decode_${decode_set}_${LM}
# Nbest rescoring
rnnlm/lmrescore_nbest.sh \
--cmd "$decode_cmd --mem 8G" --N 20 \
0.4 data/lang_test_$LM $dir \
data/${decode_set}_hires ${decode_dir} \
exp/chain_cleaned/tdnn_1d_sp/decode_${decode_set}_${LM}_${decode_dir_suffix}_nbest_rescore
done
done
fi

Expand Down