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vijayaditya merged 3 commits into from
Jan 7, 2017
Merged

add reverberated TDNN+LSTM recipe on AMI; a fix to aspire recipe #1314

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02b092a
add reverberated TDNN+LSTM recipe on AMI; a fix to aspire recipe
tomkocse Jan 4, 2017
d3a2448
add script version number
tomkocse Jan 5, 2017
ba71af4
Merge branch 'master' into ami_rvb2
vijayaditya Jan 7, 2017
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9 changes: 8 additions & 1 deletion egs/ami/s5b/RESULTS_ihm
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Expand Up @@ -69,7 +69,7 @@ for d in exp/ihm/chain/tdnn_sp_bi/decode_*; do grep Sum $d/*sc*/*ys | utils/best
%WER 22.4 | 13098 94476 | 80.4 10.4 9.2 2.8 22.4 54.6 | 0.069 | exp/ihm/chain/tdnn_sp_bi/decode_dev/ascore_10/dev_hires.ctm.filt.sys
%WER 22.5 | 12643 89974 | 80.0 12.1 7.9 2.6 22.5 52.8 | 0.157 | exp/ihm/chain/tdnn_sp_bi/decode_eval/ascore_10/eval_hires.ctm.filt.sys

# local/chain/multi_condition/run_tdnn.sh --mic ihm &
# local/chain/multi_condition/run_tdnn.sh --mic ihm
# cleanup + chain TDNN model + IHM reverberated data
# for d in exp/ihm/chain_cleaned_rvb/tdnn_sp_bi/decode_*; do grep Sum $d/*sc*/*ys | utils/best_wer.sh; done
%WER 21.5 | 13098 94486 | 81.8 11.0 7.2 3.3 21.5 54.6 | 0.090 | exp/ihm/chain_cleaned_rvb/tdnn_sp_rvb_bi/decode_dev/ascore_10/dev_hires.ctm.filt.sys
Expand All @@ -80,3 +80,10 @@ for d in exp/ihm/chain/tdnn_sp_bi/decode_*; do grep Sum $d/*sc*/*ys | utils/best
# cleanup + chain TDNN+LSTM model
%WER 20.8 | 13098 94489 | 82.0 10.0 8.0 2.8 20.8 53.2 | -0.096 | exp/ihm/chain_cleaned/tdnn_lstm1i_sp_bi_ld5/decode_dev/ascore_11/dev_hires.ctm.filt.sys
%WER 20.7 | 12643 89980 | 81.7 11.5 6.8 2.5 20.7 51.8 | 0.015 | exp/ihm/chain_cleaned/tdnn_lstm1i_sp_bi_ld5/decode_eval/ascore_11/eval_hires.ctm.filt.sys


# local/chain/multi_condition/tuning/run_tdnn_lstm_1a.sh --mic ihm
# cleanup + chain TDNN+LSTM model + IHM reverberated data
%WER 19.4 | 13098 94479 | 83.8 10.0 6.1 3.2 19.4 51.8 | -0.168 | exp/ihm/chain_cleaned_rvb/tdnn_lstm1i_sp_rvb_bi/decode_dev/ascore_10/dev_hires.ctm.filt.sys
%WER 19.3 | 12643 89977 | 83.3 11.0 5.7 2.6 19.3 49.6 | -0.046 | exp/ihm/chain_cleaned_rvb/tdnn_lstm1i_sp_rvb_bi/decode_eval/ascore_10/eval_hires.ctm.filt.sys

9 changes: 8 additions & 1 deletion egs/ami/s5b/RESULTS_mdm
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Expand Up @@ -86,6 +86,13 @@

# local/chain/tuning/run_tdnn_lstm_1i.sh --mic mdm8 --use-ihm-ali true --train-set train_cleaned --gmm tri3_cleaned
# cleanup + chain TDNN+LSTM model, MDM audio and alignments from IHM data
# *** best system ***
%WER 34.6 | 15116 94508 | 69.6 17.6 12.9 4.1 34.6 62.3 | 0.687 | exp/mdm8/chain_cleaned/tdnn_lstm1i_sp_bi_ihmali_ld5/decode_dev/ascore_9/dev_hires_o4.ctm.filt.sys
%WER 37.1 | 14343 90002 | 66.3 18.8 14.9 3.4 37.1 62.3 | 0.659 | exp/mdm8/chain_cleaned/tdnn_lstm1i_sp_bi_ihmali_ld5/decode_eval/ascore_9/eval_hires_o4.ctm.filt.sys


# local/chain/multi_condition/tuning/run_tdnn_lstm_1a.sh --mic mdm8 --use-ihm-ali true --train-set train_cleaned --gmm tri3_cleaned
# cleanup + chain TDNN+LSTM model, MDM original + IHM reverberated data, alignments from IHM data
# *** best system ***
%WER 31.8 | 14488 94497 | 71.8 15.4 12.8 3.5 31.8 62.7 | 0.698 | exp/mdm8/chain_cleaned_rvb/tdnn_lstm1i_sp_rvb_bi_ihmali/decode_dev/ascore_10/dev_hires_o4.ctm.filt.sys
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@vijayaditya vijayaditya Jan 4, 2017

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@tomkocse Very impressive results. Please add the version number of your script which generates these results (eg. run_tdnn_lstm_1a.sh ) as we might replace run_tdnn_lstm.sh with a better tdnn_lstm architecture in the future.

Move this script to tuning directory as run_tdnn_lstm_1b.sh and softlink it from run_tdnn_lstm.sh

%WER 34.2 | 13832 89953 | 68.8 16.5 14.7 3.0 34.2 62.4 | 0.669 | exp/mdm8/chain_cleaned_rvb/tdnn_lstm1i_sp_rvb_bi_ihmali/decode_eval/ascore_10/eval_hires_o4.ctm.filt.sys

14 changes: 10 additions & 4 deletions egs/ami/s5b/RESULTS_sdm
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Expand Up @@ -79,16 +79,22 @@
%WER 40.7 | 14549 94520 | 63.6 21.4 15.0 4.3 40.7 66.2 | 0.617 | exp/sdm1/chain/tdnn_sp_bi_ihmali/decode_dev/ascore_8/dev_hires_o4.ctm.filt.sys
%WER 45.1 | 13296 89971 | 59.1 23.4 17.6 4.2 45.1 69.5 | 0.591 | exp/sdm1/chain/tdnn_sp_bi_ihmali/decode_eval/ascore_8/eval_hires_o4.ctm.filt.sys

# local/chain/multi_condition/run_tdnn.sh --mic sdm1 --use-ihm-ali true --train-set train_cleaned --gmm tri3_cleaned &
# local/chain/multi_condition/run_tdnn.sh --mic sdm1 --use-ihm-ali true --train-set train_cleaned --gmm tri3_cleaned
# cleanup + chain TDNN model, SDM original + IHM reverberated data, alignments from ihm data.
# *** best system ***
# for d in exp/sdm1/chain_cleaned_rvb/tdnn_sp_rvb_bi_ihmali/decode_*; do grep Sum $d/*sc*/*ys | utils/best_wer.sh; done
%WER 38.6 | 14760 94502 | 65.3 19.3 15.4 3.9 38.6 64.9 | 0.599 | exp/sdm1/chain_cleaned_rvb/tdnn_sp_rvb_bi_ihmali/decode_dev/ascore_9/dev_hires_o4.ctm.filt.sys
%WER 42.7 | 14070 89982 | 60.9 21.0 18.0 3.6 42.7 64.5 | 0.571 | exp/sdm1/chain_cleaned_rvb/tdnn_sp_rvb_bi_ihmali/decode_eval/ascore_9/eval_hires_o4.ctm.filt.sys


# local/chain/tuning/run_tdnn_lstm_1i.sh --mic sdm1 --use-ihm-ali true --train-set train_cleaned --gmm tri3_cleaned
# cleanup + chain TDNN model, SDM audio + alignments from ihm data.
# *** best system ***
# cleanup + chain TDNN+LSTM model, SDM audio + alignments from ihm data.
%WER 37.6 | 15122 94495 | 66.1 18.7 15.1 3.7 37.6 63.2 | 0.646 | exp/sdm1/chain_cleaned/tdnn_lstm1i_sp_bi_ihmali_ld5/decode_dev/ascore_10/dev_hires_o4.ctm.filt.sys
%WER 40.9 | 13807 89961 | 62.4 20.0 17.6 3.3 40.9 65.7 | 0.612 | exp/sdm1/chain_cleaned/tdnn_lstm1i_sp_bi_ihmali_ld5/decode_eval/ascore_10/eval_hires_o4.ctm.filt.sys


# local/chain/multi_condition/tuning/run_tdnn_lstm_1a.sh --mic sdm1 --use-ihm-ali true --train-set train_cleaned --gmm tri3_cleaned
# cleanup + chain TDNN+LSTM model, SDM original + IHM reverberated data, alignments from ihm data.
# *** best system ***
%WER 34.0 | 14455 94497 | 69.8 17.7 12.5 3.8 34.0 63.9 | 0.675 | exp/sdm1/chain_cleaned_rvb/tdnn_lstm1i_sp_rvb_bi_ihmali/decode_dev/ascore_10/dev_hires_o4.ctm.filt.sys
%WER 37.5 | 13261 89982 | 65.9 19.3 14.7 3.5 37.5 66.2 | 0.642 | exp/sdm1/chain_cleaned_rvb/tdnn_lstm1i_sp_rvb_bi_ihmali/decode_eval/ascore_10/eval_hires_o4.ctm.filt.sys

6 changes: 3 additions & 3 deletions egs/ami/s5b/local/chain/multi_condition/run_tdnn.sh
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@@ -1,9 +1,9 @@
#!/bin/bash

# This is a chain-training script with TDNN neural networks.
# This script is based on local/chain/run_tdnn.sh, but adding
# This script is based on local/chain/tuning/run_tdnn_1a.sh, but adding
# the reverberated IHM data into the train set.
# This script obtains better results on both IHM and SDM tasks.
# This script obtains better results on IHM, SDM and MDM tasks.

# Please see RESULTS_* for examples of command lines invoking this script.

Expand All @@ -20,7 +20,7 @@ stage=1
mic=ihm
nj=30
min_seg_len=1.55
use_ihm_ali=true
use_ihm_ali=false
train_set=train_cleaned
gmm=tri3_cleaned # the gmm for the target data
ihm_gmm=tri3_cleaned # the gmm for the IHM system (if --use-ihm-ali true).
Expand Down
1 change: 1 addition & 0 deletions egs/ami/s5b/local/chain/multi_condition/run_tdnn_lstm.sh
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@@ -0,0 +1 @@
tuning/run_tdnn_lstm_1a.sh
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