зеркало из https://github.com/mozilla/kaldi.git
Fix to SGMM training scripts.
git-svn-id: https://svn.code.sf.net/p/kaldi/code/trunk@91 5e6a8d80-dfce-4ca6-a32a-6e07a63d50c8
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@ -43,12 +43,13 @@ exp/decode_sgmma/wer:Average WER is 3.151680 (395 / 12533)
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exp/decode_sgmma_fmllr/wer:Average WER is 2.768691 (347 / 12533)
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# sgmmb is SGMM with speaker vectors.
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exp/decode_sgmmb/wer:Average WER is 2.680922 (336 / 12533)
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exp/decode_sgmmb_utt/wer:Average WER is 2.728796 (342 / 12533)
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exp/decode_sgmmb_fmllr/wer:Average WER is 2.553259 (320 / 12533)
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exp/decode_sgmmb/wer:Average WER is 2.617091 (328 / 12533)
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exp/decode_sgmmb_utt/wer:Average WER is 2.696880 (338 / 12533)
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exp/decode_sgmmb_fmllr/wer:Average WER is 2.505386 (314 / 12533)
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# sgmmc is as sgmmb but with gender-dependent UBM, with 250
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# Gaussians per gender instead of 400 Gaussians. Note: use
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# gender info in test.
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exp/decode_sgmmc/wer:Average WER is 2.593154 (325 / 12533)
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exp/decode_sgmmc_fmllr/wer:Average WER is 2.473470 (310 / 12533)
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exp/decode_sgmmc/wer:Average WER is 2.784649 (349 / 12533)
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exp/decode_sgmmc_fmllr/wer:Average WER is 2.688901 (337 / 12533)
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@ -110,7 +110,10 @@ steps/train_ubma.sh
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(steps/train_sgmma.sh; steps/decode_sgmma.sh)&
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# train and test system with speaker vectors.
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(steps/train_sgmmb.sh; steps/decode_sgmmb.sh; steps/decode_sgmmb_fmllr.sh )&
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(steps/train_sgmmb.sh; steps/decode_sgmmb.sh; steps/decode_sgmmb_fmllr.sh; steps/decode_sgmmb_utt.sh )&
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# + gender dependency.
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(steps/train_sgmmc.sh; steps/decode_sgmmc.sh; steps/decode_sgmmc_fmllr.sh )&
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@ -120,7 +120,8 @@ while [ $iter -lt $numiters ]; do
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weight-silence-post 0.01 $silphonelist $dir/$iter.mdl ark:- ark:- | \
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sgmm-est-spkvecs $spk2utt_opt $spkvecs_opt "$gselect_opt" \
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--rand-prune=$randprune $dir/$iter.mdl \
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"$feats" ark:- ark:$dir/cur.vecs ) 2>$dir/spkvecs.$iter.log || exit 1;
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"$feats" ark:- ark:$dir/tmp.vecs ) 2>$dir/spkvecs.$iter.log || exit 1;
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mv $dir/tmp.vecs $dir/cur.vecs
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spkvecs_opt="--spk-vecs=ark:$dir/cur.vecs"
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fi
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if [ $iter -eq 0 ]; then
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@ -126,7 +126,8 @@ while [ $iter -lt $numiters ]; do
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weight-silence-post 0.01 $silphonelist $dir/$iter.mdl ark:- ark:- | \
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sgmm-est-spkvecs $spk2utt_opt $spkvecs_opt "$gselect_opt" \
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--rand-prune=$randprune $dir/$iter.mdl \
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"$feats" ark:- ark:$dir/cur.vecs ) 2>$dir/spkvecs.$iter.log || exit 1;
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"$feats" ark:- ark:$dir/tmp.vecs ) 2>$dir/spkvecs.$iter.log || exit 1;
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mv $dir/tmp.vecs $dir/cur.vecs
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spkvecs_opt="--spk-vecs=ark:$dir/cur.vecs"
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fi
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if [ $iter -eq 0 ]; then
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