Merge pull request #148 from yt605155624/add_typehint

add sclite test for text_frontend

examples/text_frontend/README.md

@@ -11,6 +11,10 @@ For text normalization, the test data is  `data/textnorm_test_cases.txt`, we use
 
 We use `CER` as evaluation criterion.
 ## Start
+If you want to use sclite to get more detail information of WER, you should run the command below to make sclite first.
+```bash
+./make_sclite.sh
+```
 Run the command below to get the results of test.
 ```bash
 ./run.sh

examples/text_frontend/make_sclite.sh

@@ -0,0 +1,13 @@
+#!/bin/bash
+
+if [ ! -d "./SCTK" ];then
+    echo "Clone SCTK ..."
+    git clone https://github.com/usnistgov/SCTK
+    echo "Clone SCTK done!"
+fi
+
+if [ ! -d "./SCTK/bin" ];then
+    echo "Start make SCTK ..."
+    pushd SCTK && make config && make all && make check && make install && make doc && popd
+    echo "SCTK make done!"
+fi

examples/text_frontend/run.sh

@@ -1,14 +1,25 @@
 #!/bin/bash
 
+USE_SCLITE=true
+
 # test g2p
-echo "Start get g2p test data."
+echo "Start get g2p test data ..."
 python3 get_g2p_data.py --root-dir=~/datasets/BZNSYP --output-dir=data/g2p
-echo "Start test g2p."
+echo "Start test g2p ..."
 python3 test_g2p.py --input-dir=data/g2p --output-dir=exp/g2p
 
 # test text normalization
-echo "Start get text normalization test data."
+echo "Start get text normalization test data ..."
 python3 get_textnorm_data.py --test-file=data/textnorm_test_cases.txt --output-dir=data/textnorm
-echo "Start test text normalization."
+echo "Start test text normalization ..."
 python3 test_textnorm.py --input-dir=data/textnorm --output-dir=exp/textnorm
 
+# whether use sclite to get more detail information of WER
+if [ "$USE_SCLITE" = true ];then
+    echo "Start sclite g2p ..."
+    ./SCTK/bin/sclite -i wsj -r ./exp/g2p/text.ref.clean trn -h ./exp/g2p/text.g2p trn -e utf-8 -o all
+    echo
+
+    echo "Start sclite textnorm ..."
+    ./SCTK/bin/sclite -i wsj -r ./exp/textnorm/text.ref.clean trn -h ./exp/textnorm/text.tn trn -e utf-8 -o all
+fi

examples/text_frontend/test_g2p.py

@@ -47,8 +47,8 @@ def get_avg_wer(raw_dict, ref_dict, frontend, output_dir):
         gt_phones = [phn for phn in gt_phones if phn not in SILENCE_TOKENS]
         gt_phones = " ".join(gt_phones)
         g2p_phones = " ".join(g2p_phones)
-        wf_ref.write(utt_id + " " + gt_phones + "\n")
+        wf_ref.write(gt_phones + "(baker_" + utt_id + ")" + "\n")
-        wf_g2p.write(utt_id + " " + g2p_phones + "\n")
+        wf_g2p.write(g2p_phones + "(baker_" + utt_id + ")" + "\n")
         edit_distance, ref_len = word_errors(gt_phones, g2p_phones)
         edit_distances.append(edit_distance)
         ref_lens.append(ref_len)

examples/text_frontend/test_textnorm.py

@@ -43,8 +43,8 @@ def get_avg_cer(raw_dict, ref_dict, text_normalizer, output_dir):
 
         gt_text = del_en_add_space(gt_text)
         textnorm_text = del_en_add_space(textnorm_text)
-        wf_ref.write(text_id + " " + gt_text + "\n")
+        wf_ref.write(gt_text + "(" + text_id + ")" + "\n")
-        wf_tn.write(text_id + " " + textnorm_text + "\n")
+        wf_tn.write(textnorm_text + "(" + text_id + ")" + "\n")
         edit_distance, ref_len = char_errors(gt_text, textnorm_text)
         edit_distances.append(edit_distance)
         ref_lens.append(ref_len)