Revised structure of rhythm prediction, test=tts

examples/other/rhy/README.md

@@ -20,6 +20,22 @@
 ## Pretrained Model
 The pretrained model can be downloaded here:
 
-[ernie-1.0_aishellcsmsc_ckpt_1.3.0](https://paddlespeech.bj.bcebos.com/Parakeet/released_models/rhy_predict/ernie-1.0_aishellcsmsc_ckpt_1.3.0.zip)
+[ernie-1.0_aishellcsmsc_ckpt_1.3.0.zip](https://paddlespeech.bj.bcebos.com/Parakeet/released_models/rhy_predict/ernie-1.0_aishellcsmsc_ckpt_1.3.0.zip)
 
 And you should put it into `exp/YOUREXP/checkpoints` folder.
+
+## Rhythm mapping
+Four punctuation marks are used to denote the rhythm marks respectively:
+|ryh_token|csmsc|aishll3|
+|:---: |:---: |:---: |
+|%|#1|%|
+|`|#2||
+|~|#3||
+|$|#4|$|
+
+## Prediction Results
+|       |  #1  |  #2 |  #3  |  #4  |
+|:-----:|:-----:|:-----:|:-----:|:-----:|  
+|Precision  |0.90  |0.66  |0.91  |0.90|
+|Recall     |0.92  |0.62  |0.83  |0.85|
+|F1         |0.91  |0.64  |0.87  |0.87|

examples/other/rhy/conf/default.yaml

@@ -2,14 +2,14 @@
 #                       DATA SETTING                      #
 ###########################################################
 dataset_type: Ernie
-train_path: data/rhy_predict/train.txt
+train_path: data/train.txt
-dev_path: data/rhy_predict/dev.txt
+dev_path: data/dev.txt
-test_path: data/rhy_predict/test.txt
+test_path: data/test.txt
 batch_size: 64
 num_workers: 2
 data_params: 
     pretrained_token: ernie-1.0
-    punc_path: data/rhy_predict/rhy_token
+    punc_path: data/rhy_token
     seq_len: 100
 
 

examples/other/rhy/local/preprocess.py

@@ -1,29 +0,0 @@
-import argparse
-
-
-def process_sentence(line):
-    if line == '':
-        return ''
-    res = line[0]
-    for i in range(1, len(line)):
-        res += (' ' + line[i])
-    return res
-
-
-if __name__ == "__main__":
-    paser = argparse.ArgumentParser(description="Input filename")
-    paser.add_argument('-input_file')
-    paser.add_argument('-output_file')
-    sentence_cnt = 0
-    args = paser.parse_args()
-    with open(args.input_file, 'r') as f:
-        with open(args.output_file, 'w') as write_f:
-            while True:
-                line = f.readline()
-                if line:
-                    sentence_cnt += 1
-                    write_f.write(process_sentence(line))
-                else:
-                    break
-    print('preprocess over')
-    print('total sentences number:', sentence_cnt)

examples/other/rhy/local/test.sh

@@ -3,9 +3,11 @@
 config_path=$1
 train_output_path=$2
 ckpt_name=$3
+print_eval=$4
 
 ckpt_prefix=${ckpt_name%.*}
 
 python3 ${BIN_DIR}/test.py \
     --config=${config_path} \
-    --checkpoint=${train_output_path}/checkpoints/${ckpt_name}
+    --checkpoint=${train_output_path}/checkpoints/${ckpt_name} \
+    --print_eval=${print_eval}

examples/other/rhy/run.sh

@@ -2,18 +2,19 @@
 set -e
 source path.sh
 
-gpus=1
+gpus=0
 stage=0
 stop_stage=100
 
 aishell_data=label_train-set.txt
 csmsc_data=000001-010000.txt
-processed_path=data/rhy_predict
+processed_path=data
 
 conf_path=conf/default.yaml
 train_output_path=exp/rhy
 ckpt_name=snapshot_iter_2600.pdz
 text=我们城市的复苏有赖于他强有力的政策。
+print_eval=false
 
 # with the following command, you can choose the stage range you want to run
 # such as `./run.sh --stage 0 --stop-stage 0`
@@ -31,7 +32,7 @@ if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
 fi
 
 if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
-   CUDA_VISIBLE_DEVICES=${gpus} ./local/test.sh ${conf_path} ${train_output_path} ${ckpt_name} || exit -1
+   CUDA_VISIBLE_DEVICES=${gpus} ./local/test.sh ${conf_path} ${train_output_path} ${ckpt_name} ${print_eval} || exit -1
 fi
 
 if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then

paddlespeech/text/exps/ernie_linear/test.py

@@ -26,6 +26,8 @@ from yacs.config import CfgNode
 from paddlespeech.text.models.ernie_linear import ErnieLinear
 from paddlespeech.text.models.ernie_linear import PuncDataset
 from paddlespeech.text.models.ernie_linear import PuncDatasetFromErnieTokenizer
+from paddlespeech.t2s.utils import str2bool
+
 
 DefinedClassifier = {
     'ErnieLinear': ErnieLinear,
@@ -91,9 +93,12 @@ def test(args):
     t = classification_report(
         test_total_label, test_total_predict, target_names=punc_list)
     print(t)
+    if args.print_eval:
         t2 = evaluation(test_total_label, test_total_predict)
         print('=========================================================')
         print(t2)
+    else:
+        pass
 
 
 def main():
@@ -101,6 +106,10 @@ def main():
     parser = argparse.ArgumentParser(description="Test a ErnieLinear model.")
     parser.add_argument("--config", type=str, help="ErnieLinear config file.")
     parser.add_argument("--checkpoint", type=str, help="snapshot to load.")
+    parser.add_argument(
+        "--print_eval",
+        type=str2bool,
+        default=False)
     parser.add_argument(
         "--ngpu", type=int, default=1, help="if ngpu=0, use cpu.")