add scripts

speechx/examples/u2pp_ol/wenetspeech/.gitignore

@@ -0,0 +1,3 @@
+data
+utils
+exp

speechx/examples/u2pp_ol/wenetspeech/README.md

@@ -0,0 +1,28 @@
+# u2/u2pp Streaming ASR 
+
+## Testing with Aishell Test Data
+
+## Download wav and model
+
+```
+run.sh --stop_stage 0
+```
+
+### compute feature
+
+```
+./run.sh --stage 1 --stop_stage 1
+```
+
+### decoding using feature
+
+```
+./run.sh --stage 2 --stop_stage 2
+```
+
+### decoding using wav
+
+
+```
+./run.sh --stage 3 --stop_stage 3
+```

speechx/examples/u2pp_ol/wenetspeech/local/aishell_train_lms.sh

@@ -0,0 +1,71 @@
+#!/bin/bash
+
+# To be run from one directory above this script.
+. ./path.sh
+
+nj=40
+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
+
+# oov to <SPOKEN_NOISE>
+# lexicon line: word char0 ... charn
+# text line: utt word0 ... wordn -> line: <SPOKEN_NOISE> word0 ... wordn
+text_dir=$(dirname $text)
+split_name=$(basename $text)
+./local/split_data.sh $text_dir $text $split_name $nj
+
+utils/run.pl JOB=1:$nj $text_dir/split${nj}/JOB/${split_name}.no_oov.log \
+  cat ${text_dir}/split${nj}/JOB/${split_name} \| awk -v lex=$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");}' \
+    \> ${text_dir}/split${nj}/JOB/${split_name}.no_oov || exit 1;
+cat ${text_dir}/split${nj}/*/${split_name}.no_oov  > $cleantext
+
+# compute word counts, sort in descending order
+# line: count word
+cat $cleantext | awk '{for(n=2;n<=NF;n++) print $n; }' | sort --parallel=`nproc` | uniq -c | \
+   sort --parallel=`nproc` -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 --parallel=`nproc` | uniq -c | sort --parallel=`nproc` -nr > $dir/unigram.counts || exit 1;
+
+# word with <s> </s>
+cat $dir/unigram.counts | awk '{print $2}' | cat - <(echo "<s>"; echo "</s>" ) > $dir/wordlist
+
+# hold out to compute ppl
+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/u2pp_ol/wenetspeech/local/decode.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -e
+
+. path.sh
+
+data=data
+exp=exp
+nj=20
+mkdir -p $exp
+ckpt_dir=./data/model
+model_dir=$ckpt_dir/asr1_chunk_conformer_u2pp_wenetspeech_static_1.1.0.model/
+
+utils/run.pl JOB=1:$nj $data/split${nj}/JOB/decoder.fbank.wolm.log \
+ctc_prefix_beam_search_decoder_main \
+    --model_path=$model_dir/export.jit \
+    --vocab_path=$model_dir/unit.txt \
+    --nnet_decoder_chunk=16 \
+    --receptive_field_length=7 \
+    --subsampling_rate=4 \
+    --feature_rspecifier=scp:$data/split${nj}/JOB/fbank.scp \
+    --result_wspecifier=ark,t:$data/split${nj}/JOB/result_decode.ark
+
+cat $data/split${nj}/*/result_decode.ark > $exp/${label_file}
+utils/compute-wer.py --char=1 --v=1 $text $exp/${label_file} > $exp/${wer}
+tail -n 7 $exp/${wer}

speechx/examples/u2pp_ol/wenetspeech/local/feat.sh

@@ -0,0 +1,31 @@
+#!/bin/bash
+set -e
+
+. path.sh
+
+data=data
+exp=exp
+nj=20
+mkdir -p $exp
+ckpt_dir=./data/model
+model_dir=$ckpt_dir/asr1_chunk_conformer_u2pp_wenetspeech_static_1.1.0.model/
+aishell_wav_scp=aishell_test.scp
+
+cmvn_json2kaldi_main \
+    --json_file  $model_dir/mean_std.json \
+    --cmvn_write_path $exp/cmvn.ark \
+    --binary=false
+
+echo "convert json cmvn to kaldi ark."
+
+./local/split_data.sh $data $data/$aishell_wav_scp $aishell_wav_scp $nj
+
+utils/run.pl JOB=1:$nj $data/split${nj}/JOB/feat.log \
+compute_fbank_main \
+    --num_bins 80 \
+    --cmvn_file=$exp/cmvn.ark \
+    --streaming_chunk=36 \
+    --wav_rspecifier=scp:$data/split${nj}/JOB/${aishell_wav_scp} \
+    --feature_wspecifier=ark,scp:$data/split${nj}/JOB/fbank.ark,$data/split${nj}/JOB/fbank.scp
+
+echo "compute fbank feature."

speechx/examples/u2pp_ol/wenetspeech/local/nnet.sh

@@ -0,0 +1,23 @@
+#!/bin/bash
+set -x
+set -e
+
+. path.sh
+
+data=data
+exp=exp
+mkdir -p $exp
+ckpt_dir=./data/model
+model_dir=$ckpt_dir/asr1_chunk_conformer_u2pp_wenetspeech_static_1.1.0.model/
+
+u2_nnet_main \
+    --model_path=$model_dir/export.jit \
+    --feature_rspecifier=ark,t:$exp/fbank.ark \
+    --nnet_decoder_chunk=16 \
+    --receptive_field_length=7 \
+    --subsampling_rate=4 \
+    --acoustic_scale=1.0 \
+    --nnet_encoder_outs_wspecifier=ark,t:$exp/encoder_outs.ark \
+    --nnet_prob_wspecifier=ark,t:$exp/logprobs.ark
+echo "u2 nnet decode."
+

speechx/examples/u2pp_ol/wenetspeech/local/recognizer.sh

@@ -0,0 +1,34 @@
+#!/bin/bash
+set -e
+
+. path.sh
+
+data=data
+exp=exp
+nj=20
+mkdir -p $exp
+ckpt_dir=./data/model
+model_dir=$ckpt_dir/asr1_chunk_conformer_u2pp_wenetspeech_static_1.1.0.model/
+aishell_wav_scp=aishell_test.scp
+
+./local/split_data.sh $data $data/$aishell_wav_scp $aishell_wav_scp $nj
+
+utils/run.pl JOB=1:$nj $data/split${nj}/JOB/recognizer.log \
+u2_recognizer_main \
+    --use_fbank=true \
+    --num_bins=80 \
+    --cmvn_file=$exp/cmvn.ark \
+    --model_path=$model_dir/export.jit \
+    --vocab_path=$model_dir/unit.txt \
+    --nnet_decoder_chunk=16 \
+    --receptive_field_length=7 \
+    --subsampling_rate=4 \
+    --wav_rspecifier=scp:$data/split${nj}/JOB/${aishell_wav_scp} \
+    --result_wspecifier=ark,t:$data/split${nj}/JOB/result_recognizer.ark
+
+
+cat $data/split${nj}/*/result_recognizer.ark > $exp/${label_file}_recognizer
+utils/compute-wer.py --char=1 --v=1 $text $exp/${label_file}_recognizer > $exp/${wer}.recognizer
+echo "recognizer test have finished!!!"
+echo "please checkout in ${exp}/${wer}.recognizer"
+tail -n 7 $exp/${wer}.recognizer

speechx/examples/u2pp_ol/wenetspeech/local/split_data.sh

@@ -0,0 +1,30 @@
+#!/usr/bin/env bash
+
+set -eo pipefail
+
+data=$1
+scp=$2
+split_name=$3
+numsplit=$4
+
+# save in $data/split{n}
+# $scp to split
+# 
+
+if [[ ! $numsplit -gt 0 ]]; then
+  echo "$0: Invalid num-split argument";
+  exit 1;
+fi
+
+directories=$(for n in `seq $numsplit`; do echo $data/split${numsplit}/$n; done)
+scp_splits=$(for n in `seq $numsplit`; do echo $data/split${numsplit}/$n/${split_name}; done)
+
+# if this mkdir fails due to argument-list being too long, iterate.
+if ! mkdir -p $directories >&/dev/null; then
+  for n in `seq $numsplit`; do
+    mkdir -p $data/split${numsplit}/$n
+  done
+fi
+
+echo "utils/split_scp.pl $scp $scp_splits"
+utils/split_scp.pl $scp $scp_splits

speechx/examples/u2pp_ol/wenetspeech/path.sh

@@ -0,0 +1,18 @@
+# This contains the locations of binarys build required for running the examples.
+
+unset GREP_OPTIONS
+
+SPEECHX_ROOT=$PWD/../../../
+SPEECHX_BUILD=$SPEECHX_ROOT/build/speechx
+
+SPEECHX_TOOLS=$SPEECHX_ROOT/tools
+TOOLS_BIN=$SPEECHX_TOOLS/valgrind/install/bin
+
+[ -d $SPEECHX_BUILD ] || { echo "Error: 'build/speechx' directory not found. please ensure that the project build successfully"; }
+
+export LC_AL=C
+
+export PATH=$PATH:$TOOLS_BIN:$SPEECHX_BUILD/nnet:$SPEECHX_BUILD/decoder:$SPEECHX_BUILD/frontend/audio
+
+PADDLE_LIB_PATH=$(python -c "import paddle ; print(':'.join(paddle.sysconfig.get_lib()), end='')")
+export LD_LIBRARY_PATH=$PADDLE_LIB_PATH:$LD_LIBRARY_PATH

speechx/examples/u2pp_ol/wenetspeech/run.sh

@@ -0,0 +1,76 @@
+#!/bin/bash
+set +x
+set -e
+
+. path.sh
+
+nj=40
+stage=0
+stop_stage=5
+
+. utils/parse_options.sh
+
+# input
+data=data
+exp=exp
+mkdir -p $exp $data
+
+
+# 1. compile
+if [ ! -d ${SPEECHX_BUILD} ]; then
+    pushd ${SPEECHX_ROOT} 
+    bash build.sh
+    popd
+fi
+
+
+ckpt_dir=$data/model
+model_dir=$ckpt_dir/asr1_chunk_conformer_u2pp_wenetspeech_static_1.1.0.model/
+
+
+if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ];then
+    #  download model
+    if [ ! -f $ckpt_dir/asr1_chunk_conformer_u2pp_wenetspeech_static_1.1.0.model.tar.gz ]; then
+        mkdir -p $ckpt_dir
+        pushd $ckpt_dir
+
+        wget -c https://paddlespeech.bj.bcebos.com/s2t/wenetspeech/asr1/static/asr1_chunk_conformer_u2pp_wenetspeech_static_1.1.0.model.tar.gz
+        tar xzfv asr1_chunk_conformer_u2pp_wenetspeech_static_1.1.0.model.tar.gz
+
+        popd
+    fi
+
+    # test wav scp
+    if [ ! -f data/wav.scp ]; then
+        mkdir -p $data
+        pushd $data
+        wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav
+        echo "utt1 " $PWD/zh.wav > wav.scp
+        popd 
+    fi
+
+    # aishell wav scp
+    if [ ! -d $data/test ]; then
+        pushd $data
+        wget -c https://paddlespeech.bj.bcebos.com/s2t/paddle_asr_online/aishell_test.zip
+        unzip  aishell_test.zip
+        popd
+
+        realpath $data/test/*/*.wav > $data/wavlist
+        awk -F '/' '{ print $(NF) }' $data/wavlist | awk -F '.' '{ print $1 }' > $data/utt_id
+        paste $data/utt_id $data/wavlist > $data/$aishell_wav_scp
+    fi
+fi
+
+
+if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
+    ./local/feat.sh
+fi
+
+if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
+    ./local/decode.sh
+fi
+
+if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
+    ./loca/recognizer.sh
+fi