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Allow segmentation with nnet3 chain models #2845

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Nov 17, 2018
Merged

Allow segmentation with nnet3 chain models #2845

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17 changes: 11 additions & 6 deletions egs/wsj/s5/steps/cleanup/clean_and_segment_data_nnet3.sh
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Original file line number Diff line number Diff line change
Expand Up @@ -26,6 +26,10 @@ graph_opts=
beam=15.0
lattice_beam=1.0

acwt=0.1 # Just a default value, used for adaptation and beam-pruning..
post_decode_acwt=1.0 # can be used in 'chain' systems to scale acoustics by 10 so the
# regular scoring script works.

# Contexts must ideally match training
extra_left_context=0 # Set to some large value, typically 40 for LSTM (must match training)
extra_right_context=0
Expand All @@ -36,7 +40,7 @@ frames_per_chunk=150
# i-vector options
extractor= # i-Vector extractor. If provided, will extract i-vectors.
# Required if the network was trained with i-vector extractor.
use_vad= # Use energy-based VAD for i-vector extraction
use_vad=false # Use energy-based VAD for i-vector extraction

segmentation_opts=

Expand Down Expand Up @@ -119,25 +123,26 @@ fi

online_ivector_dir=
if [ ! -z "$extractor" ]; then
online_ivector_dir=$dir/ivectors_$(basename $data_uniform_seg)
online_ivector_dir=$dir/ivectors_$(basename $data)

if [ $stage -le 2 ]; then
# Compute energy-based VAD
if $use_vad; then
steps/compute_vad_decision.sh $data_uniform_seg \
$data_uniform_seg/log $data_uniform_seg/data
steps/compute_vad_decision.sh $data \
$data/log $data/data
fi

steps/online/nnet2/extract_ivectors_online.sh \
--nj $nj --cmd "$cmd --mem 4G" --use-vad $use_vad \
$data_uniform_seg $extractor $online_ivector_dir
$data $extractor $online_ivector_dir
fi
fi

if [ $stage -le 3 ]; then
echo "$0: Decoding with biased language models..."

steps/cleanup/decode_segmentation_nnet3.sh \
--acwt $acwt --post-decode-acwt $post_decode_acwt \
--beam $beam --lattice-beam $lattice_beam --nj $nj --cmd "$cmd --mem 4G" \
--skip-scoring true --allow-partial false \
--extra-left-context $extra_left_context \
Expand All @@ -154,7 +159,7 @@ fi

frame_shift_opt=
if [ -f $srcdir/frame_subsampling_factor ]; then
frame_shift_opt="--frame-shift=0.0$(cat $srcdir/frame_subsampling_factor)"
frame_shift_opt="--frame-shift 0.0$(cat $srcdir/frame_subsampling_factor)"
fi

if [ $stage -le 4 ]; then
Expand Down
9 changes: 7 additions & 2 deletions egs/wsj/s5/steps/cleanup/segment_long_utterances_nnet3.sh
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Original file line number Diff line number Diff line change
Expand Up @@ -43,6 +43,10 @@ beam=15.0
lattice_beam=1.0
lmwt=10

acwt=0.1 # Just a default value, used for adaptation and beam-pruning..
post_decode_acwt=1.0 # can be used in 'chain' systems to scale acoustics by 10 so the
# regular scoring script works.

# Contexts must ideally match training
extra_left_context=0 # Set to some large value, typically 40 for LSTM (must match training)
extra_right_context=0
Expand All @@ -53,7 +57,7 @@ frames_per_chunk=150
# i-vector options
extractor= # i-Vector extractor. If provided, will extract i-vectors.
# Required if the network was trained with i-vector extractor.
use_vad= # Use energy-based VAD for i-vector extraction
use_vad=false # Use energy-based VAD for i-vector extraction

# TF-IDF similarity search options
max_words=1000
Expand Down Expand Up @@ -263,6 +267,7 @@ if [ $stage -le 5 ]; then
echo "$0: Decoding with biased language models..."

steps/cleanup/decode_segmentation_nnet3.sh \
--acwt $acwt --post-decode-acwt $post_decode_acwt \
--beam $beam --lattice-beam $lattice_beam --nj $nj --cmd "$cmd --mem 4G" \
--skip-scoring true --allow-partial false \
--extra-left-context $extra_left_context \
Expand All @@ -276,7 +281,7 @@ fi

frame_shift_opt=
if [ -f $srcdir/frame_subsampling_factor ]; then
frame_shift_opt="--frame-shift=0.0$(cat $srcdir/frame_subsampling_factor)"
frame_shift_opt="--frame-shift 0.0$(cat $srcdir/frame_subsampling_factor)"
fi

if [ $stage -le 6 ]; then
Expand Down