From 2bced72c1ba5d119b7ad8945573c76bb77723ae2 Mon Sep 17 00:00:00 2001
From: dohe0342 <kimdohe1070@gmail.com>
Date: Fri, 9 Jun 2023 14:49:46 +0900
Subject: [PATCH] from local

---
 egs/tedlium3/ASR/.prepare.sh.swp | Bin 16384 -> 16384 bytes
 egs/tedlium3/ASR/2               | 231 +++++++++++++++++++++++++++++++
 2 files changed, 231 insertions(+)
 create mode 100644 egs/tedlium3/ASR/2

diff --git a/egs/tedlium3/ASR/.prepare.sh.swp b/egs/tedlium3/ASR/.prepare.sh.swp
index d2be350273ffe69948045ed72a1dcf58de98b8c7..bddf02a0d88b82cf85cba0ac1e75ece3cc36ecfb 100644
GIT binary patch
delta 40
ucmZo@U~Fh$6iYG)^Ym4))H7fJ0s#hw)V)n9ssbCuZZb25ZvMb5U;_Zn<O+rW

delta 40
ucmZo@U~Fh$6iYG)^Ym4))H7fJ0s#gF!@W%@ulP5L-DGBD*!+Q6zy<))X9~dp

diff --git a/egs/tedlium3/ASR/2 b/egs/tedlium3/ASR/2
new file mode 100644
index 000000000..eb6f9ea6e
--- /dev/null
+++ b/egs/tedlium3/ASR/2
@@ -0,0 +1,231 @@
+#!/usr/bin/env bash
+
+# fix segmentation fault reported in https://github.com/k2-fsa/icefall/issues/674
+export PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python
+
+set -eou pipefail
+
+stage=0
+stop_stage=100
+
+# We assume dl_dir (download dir) contains the following
+# directories and files. If not, they will be downloaded
+# by this script automatically.
+#
+#  - $dl_dir/tedlium3
+#      You can find data, doc, legacy, LM, etc, inside it.
+#      You can download them from https://www.openslr.org/51
+#
+#  - $dl_dir/musan
+#      This directory contains the following directories downloaded from
+#       http://www.openslr.org/17/
+#
+#     - music
+#     - noise
+#     - speech
+dl_dir=/DB
+
+. shared/parse_options.sh || exit 1
+
+# vocab size for sentence piece models.
+# It will generate data/lang_bpe_xxx,
+# data/lang_bpe_yyy if the array contains xxx, yyy
+vocab_sizes=(
+  5000
+  2000
+  1000
+  500
+)
+
+# All files generated by this script are saved in "data".
+# You can safely remove "data" and rerun this script to regenerate it.
+mkdir -p data
+
+log() {
+  # This function is from espnet
+  local fname=${BASH_SOURCE[1]##*/}
+  echo -e "$(date '+%Y-%m-%d %H:%M:%S') (${fname}:${BASH_LINENO[0]}:${FUNCNAME[1]}) $*"
+}
+
+log "dl_dir: $dl_dir"
+
+if [ $stage -le 0 ] && [ $stop_stage -ge 0 ]; then
+  log "Stage 0: Download data"
+
+  # If you have pre-downloaded it to /path/to/tedlium3,
+  # you can create a symlink
+  #
+  # ln -sfv /path/to/tedlium3 $dl_dir/tedlium3
+  #
+  if [ ! -d $dl_dir/tedlium3 ]; then
+    lhotse download tedlium $dl_dir
+    mv $dl_dir/TEDLIUM_release-3 $dl_dir/tedlium3
+  fi
+
+  # Download big and small 4 gram lanuage models
+  if [ ! -d $dl_dir/lm ]; then
+    wget --continue http://kaldi-asr.org/models/5/4gram_small.arpa.gz -P $dl_dir/lm
+    wget --continue http://kaldi-asr.org/models/5/4gram_big.arpa.gz -P $dl_dir/lm
+    gzip -d $dl_dir/lm/4gram_small.arpa.gz $dl_dir/lm/4gram_big.arpa.gz
+  fi
+
+  # If you have pre-downloaded it to /path/to/musan,
+  # you can create a symlink
+  #
+  #ln -sfv /path/to/musan $dl_dir/musan
+
+  if [ ! -d $dl_dir/musan ]; then
+    lhotse download musan $dl_dir
+  fi
+fi
+
+if [ $stage -le 1 ] && [ $stop_stage -ge 1 ]; then
+  log "Stage 1: Prepare tedlium3 manifests"
+  if [ ! -f data/manifests/.tedlium3.done ]; then
+    # We assume that you have downloaded the tedlium3 corpus
+    # to $dl_dir/tedlium3
+    mkdir -p data/manifests
+    lhotse prepare tedlium $dl_dir/tedlium3 data/manifests
+    touch data/manifests/.tedlium3.done
+  fi
+fi
+
+if [ $stage -le 2 ] && [ $stop_stage -ge 2 ]; then
+  log "Stage 2: Prepare musan manifests"
+  # We assume that you have downloaded the musan corpus
+  # to data/musan
+  if [ ! -e data/manifests/.musan.done ]; then
+    mkdir -p data/manifests
+    lhotse prepare musan $dl_dir/musan data/manifests
+    touch data/manifests/.musan.done
+  fi
+fi
+
+if [ $stage -le 3 ] && [ $stop_stage -ge 3 ]; then
+  log "Stage 3: Compute fbank for tedlium3"
+
+  if [ ! -e data/fbank/.tedlium3.done ]; then
+    mkdir -p data/fbank
+
+    python3 ./local/compute_fbank_tedlium.py
+
+    gunzip -c data/fbank/tedlium_cuts_train.jsonl.gz | shuf | \
+    gzip -c > data/fbank/tedlium_cuts_train-shuf.jsonl.gz
+    mv data/fbank/tedlium_cuts_train-shuf.jsonl.gz \
+       data/fbank/tedlium_cuts_train.jsonl.gz
+
+    touch data/fbank/.tedlium3.done
+  fi
+fi
+
+if [ $stage -le 4 ] && [ $stop_stage -ge 4 ]; then
+  log "Stage 4: Compute fbank for musan"
+  if [ ! -e data/fbank/.musan.done ]; then
+    mkdir -p data/fbank
+    python3 ./local/compute_fbank_musan.py
+    touch data/fbank/.musan.done
+  fi
+fi
+
+if [ $stage -le 5 ] && [ $stop_stage -ge 5 ]; then
+  log "Stage 5: Prepare BPE train data and set of words"
+  lang_dir=data/lang
+  mkdir -p $lang_dir
+
+  if [ ! -f $lang_dir/train.txt ]; then
+    gunzip -c $dl_dir/tedlium3/LM/*.en.gz | sed 's: <\/s>::g' > $lang_dir/train_orig.txt
+
+    ./local/prepare_transcripts.py \
+      --input-text-path $lang_dir/train_orig.txt \
+      --output-text-path $lang_dir/train.txt
+  fi
+
+  if [ ! -f $lang_dir/words.txt ]; then
+
+    awk '{print $1}' $dl_dir/tedlium3/TEDLIUM.152k.dic |
+    sed 's:([0-9])::g' | sort | uniq > $lang_dir/words_orig.txt
+
+    ./local/prepare_words.py --lang-dir $lang_dir
+  fi
+fi
+
+if [ $stage -le 6 ] && [ $stop_stage -ge 6 ]; then
+  log "Stage 6: Prepare BPE based lang"
+
+  for vocab_size in ${vocab_sizes[@]}; do
+    lang_dir=data/lang_bpe_${vocab_size}
+    mkdir -p $lang_dir
+    # We reuse words.txt from phone based lexicon
+    # so that the two can share G.pt later.
+    cp data/lang/words.txt $lang_dir
+
+    ./local/train_bpe_model.py \
+      --lang-dir $lang_dir \
+      --vocab-size $vocab_size \
+      --transcript data/lang/train.txt
+
+    if [ ! -f $lang_dir/L_disambig.pt ]; then
+      ./local/prepare_lang_bpe.py --lang-dir $lang_dir --oov "<unk>"
+    fi
+  done
+fi
+
+if [ $stage -le 7 ] && [ $stop_stage -ge 7 ]; then
+  log "Stage 7: Prepare G"
+  # We assume you have install kaldilm, if not, please install
+  # it using: pip install kaldilm
+
+  mkdir -p data/lm
+  if [ ! -f data/lm/G_4_gram_small.fst.txt ]; then
+    # It is used in building HLG
+    python3 -m kaldilm \
+      --read-symbol-table="data/lang/words.txt" \
+      --disambig-symbol='#0' \
+      --max-order=4 \
+      --max-arpa-warnings=-1 \
+      $dl_dir/lm/4gram_small.arpa > data/lm/G_4_gram_small.fst.txt
+  fi
+
+  if [ ! -f data/lm/G_4_gram_big.fst.txt ]; then
+    # It is used for LM rescoring
+    python3 -m kaldilm \
+      --read-symbol-table="data/lang/words.txt" \
+      --disambig-symbol='#0' \
+      --max-order=4 \
+      --max-arpa-warnings=-1 \
+      $dl_dir/lm/4gram_big.arpa > data/lm/G_4_gram_big.fst.txt
+  fi
+fi
+
+if [ $stage -le 8 ] && [ $stop_stage -ge 8 ]; then
+  log "Stage 8: Compile HLG"
+
+  for vocab_size in ${vocab_sizes[@]}; do
+    lang_dir=data/lang_bpe_${vocab_size}
+
+    if [ ! -f $lang_dir/HLG.pt ]; then
+      ./local/compile_hlg.py \
+        --lang-dir $lang_dir \
+        --lm G_4_gram_small
+    fi
+  done
+fi
+
+if [ $stage -le 9 ] && [ $stop_stage -ge 9 ]; then
+  log "Stage 9: Split cuts by speaker id"
+  gzip -d data/fbank/tedlium_cuts_test.jsonl.gz
+
+  i=0
+  for spk in $dl_dir/tedlium3/legacy/test/sph/*; do
+	  spk_id=${spk#*sph\/}
+	  spk_id=${spk_id%.sph}
+	  echo $spk_id
+	  cat data/fbank/tedlium_cuts_test.jsonl | grep speaker\":\ \"$spk_id\" > data/fbank/tedlium_cuts_test_$i.jsonl
+	  gzip data/fbank/tedlium_cuts_test_$i.jsonl
+	  i=`expr $i + 1` 
+  done
+
+  gzip data/fbank/tedlium_cuts_test.jsonl
+  #cat data/fbank/tedlium_cuts_test.jsonl.gz | grep 
+
+fi