rm example/aishell

speechx/examples/aishell/local/aishell_train_lms.sh

@@ -1,59 +0,0 @@
-#!/bin/bash
-
-
-# To be run from one directory above this script.
-. ./path.sh
-
-text=data/local/lm/text
-lexicon=data/local/dict/lexicon.txt
-
-for f in "$text" "$lexicon"; do
-  [ ! -f $x ] && echo "$0: No such file $f" && exit 1;
-done
-
-# Check SRILM tools
-if ! which ngram-count > /dev/null; then
-    echo "srilm tools are not found, please download it and install it from: "
-    echo "http://www.speech.sri.com/projects/srilm/download.html"
-    echo "Then add the tools to your PATH"
-    exit 1
-fi
-
-# This script takes no arguments.  It assumes you have already run
-# aishell_data_prep.sh.
-# It takes as input the files
-# data/local/lm/text
-# data/local/dict/lexicon.txt
-dir=data/local/lm
-mkdir -p $dir
-
-
-cleantext=$dir/text.no_oov
-
-cat $text | awk -v lex=$lexicon 'BEGIN{while((getline<lex) >0){ seen[$1]=1; } }
-  {for(n=1; n<=NF;n++) {  if (seen[$n]) { printf("%s ", $n); } else {printf("<SPOKEN_NOISE> ");} } printf("\n");}' \
-  > $cleantext || exit 1;
-
-cat $cleantext | awk '{for(n=2;n<=NF;n++) print $n; }' | sort | uniq -c | \
-   sort -nr > $dir/word.counts || exit 1;
-
-# Get counts from acoustic training transcripts, and add  one-count
-# for each word in the lexicon (but not silence, we don't want it
-# in the LM-- we'll add it optionally later).
-cat $cleantext | awk '{for(n=2;n<=NF;n++) print $n; }' | \
-  cat - <(grep -w -v '!SIL' $lexicon | awk '{print $1}') | \
-   sort | uniq -c | sort -nr > $dir/unigram.counts || exit 1;
-
-cat $dir/unigram.counts | awk '{print $2}' | cat - <(echo "<s>"; echo "</s>" ) > $dir/wordlist
-
-heldout_sent=10000 # Don't change this if you want result to be comparable with
-    # kaldi_lm results
-mkdir -p $dir
-cat $cleantext | awk '{for(n=2;n<=NF;n++){ printf $n; if(n<NF) printf " "; else print ""; }}' | \
-  head -$heldout_sent > $dir/heldout
-cat $cleantext | awk '{for(n=2;n<=NF;n++){ printf $n; if(n<NF) printf " "; else print ""; }}' | \
-  tail -n +$heldout_sent > $dir/train
-
-ngram-count -text $dir/train -order 3 -limit-vocab -vocab $dir/wordlist -unk \
-  -map-unk "<UNK>" -kndiscount -interpolate -lm $dir/lm.arpa
-ngram -lm $dir/lm.arpa -ppl $dir/heldout

speechx/examples/aishell/mkgraph.sh

@@ -1,31 +0,0 @@
-#!/bin/bash
-
-. ./path.sh || exit 1;
-
-. tools/parse_options.sh || exit 1;
-
-data=/mnt/dataset/aishell
-
-# Optionally, you can add LM and test it with runtime.
-dir=./ds2_graph
-dict=$dir/vocab.txt
-if [ ${stage} -le 7 ] && [ ${stop_stage} -ge 7 ]; then
-  # 7.1 Prepare dict
-  unit_file=$dict
-  mkdir -p $dir/local/dict
-  cp $unit_file $dir/local/dict/units.txt
-  tools/fst/prepare_dict.py $unit_file ${data}/resource_aishell/lexicon.txt \
-    $dir/local/dict/lexicon.txt
-  # Train lm
-  lm=$dir/local/lm
-  mkdir -p $lm
-  tools/filter_scp.pl data/train/text \
-    $data/data_aishell/transcript/aishell_transcript_v0.8.txt > $lm/text
-  local/ds2_aishell_train_lms.sh
-  # Build decoding TLG
-  tools/fst/compile_lexicon_token_fst.sh \
-    $dir/local/dict $dir/local/tmp $dir/local/lang
-  tools/fst/make_tlg.sh $dir/local/lm $dir/local/lang $dir/lang_test || exit 1;
-fi
-
-

speechx/examples/aishell/path.sh

@@ -1,14 +0,0 @@
-# This contains the locations of binarys build required for running the examples.
-
-SPEECHX_ROOT=$PWD/../..
-SPEECHX_EXAMPLES=$SPEECHX_ROOT/build/examples
-
-SPEECHX_TOOLS=$SPEECHX_ROOT/tools
-TOOLS_BIN=$SPEECHX_TOOLS/valgrind/install/bin
-
-[ -d $SPEECHX_EXAMPLES ] || { echo "Error: 'build/examples' directory not found. please ensure that the project build successfully"; }
-
-export LC_AL=C
-
-SPEECHX_BIN=$SPEECHX_EXAMPLES/feat
-export PATH=$PATH:$SPEECHX_BIN:$TOOLS_BIN