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egs/hkust/s5/local/nnet2/run_convnet.sh
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#!/bin/bash
# 2015 Xingyu Na
# This script runs on the full training set, using ConvNet setup on top of
# fbank features, on GPU. The ConvNet has four hidden layers, two convolutional
# layers and two affine transform layers with ReLU nonlinearity.
# Convolutional layer [1]:
# convolution1d, input feature dim is 36, filter dim is 7, output dim is
# 30, 128 filters are used
# maxpooling, 3-to-1 maxpooling, input dim is 30, output dim is 10
# Convolutional layer [2]:
# convolution1d, input feature dim is 10, filter dim is 4, output dim is
# 7, 256 filters are used
# Affine transform layers [3-4]:
# affine transform with ReLU nonlinearity.
temp_dir=
dir=exp/nnet2_convnet
stage=-5
train_original=data/train
train=data-fb/train
. ./cmd.sh
. ./path.sh
. utils/parse_options.sh
parallel_opts="--gpu 1" # This is suitable for the CLSP network, you'll
# likely have to change it.
# Make the FBANK features
if [ $stage -le -5 ]; then
# Dev set
utils/copy_data_dir.sh data/dev data-fb/dev || exit 1; rm $train/{cmvn,feats}.scp
steps/make_fbank.sh --nj 10 --cmd "$train_cmd" \
data-fb/dev data-fb/dev/log data-fb/dev/data || exit 1;
steps/compute_cmvn_stats.sh data-fb/dev data-fb/dev/log data-fb/dev/data || exit 1;
# Training set
utils/copy_data_dir.sh $train_original $train || exit 1; rm $train/{cmvn,feats}.scp
steps/make_fbank.sh --nj 10 --cmd "$train_cmd" \
$train $train/log $train/data || exit 1;
steps/compute_cmvn_stats.sh $train $train/log $train/data || exit 1;
fi
(
if [ ! -f $dir/final.mdl ]; then
steps/nnet2/train_convnet_accel2.sh --parallel-opts "$parallel_opts" \
--cmd "$decode_cmd" --stage $stage \
--num-threads 1 --minibatch-size 512 \
--mix-up 20000 --samples-per-iter 300000 \
--num-epochs 15 --delta-order 2 \
--initial-effective-lrate 0.0001 --final-effective-lrate 0.00001 \
--num-jobs-initial 3 --num-jobs-final 8 --splice-width 5 \
--hidden-dim 2000 --num-filters1 128 --patch-dim1 7 --pool-size 3 \
--num-filters2 256 --patch-dim2 4 \
$train data/lang exp/tri5a_ali $dir || exit 1;
fi
steps/nnet2/decode.sh --cmd "$decode_cmd" --nj 10 \
--config conf/decode.config \
exp/tri5a/graph data-fb/dev \
$dir/decode || exit 1;
)
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