diff --git a/examples/fastspeech/README.md b/examples/fastspeech/README.md
index 865f68ae0af04e935360eea51a704ad960626500..0c40488db4c4acf5dbc6def70aa9a5a7322fcbc3 100644
--- a/examples/fastspeech/README.md
+++ b/examples/fastspeech/README.md
@@ -126,10 +126,10 @@ python synthesis.py \
 --checkpoint=${CHECKPOINTPATH} \
 --config='configs/ljspeech.yaml' \
 --output=${OUTPUTPATH} \
---vocoder='griffinlim' \
+--vocoder='griffin-lim' \
 ```
 
-We currently support two vocoders, ``griffinlim`` and ``waveflow``. You can set ``--vocoder`` to use one of them. If you want to use ``waveflow`` as your vocoder, you need to set ``--config_vocoder`` and ``--checkpoint_vocoder`` which are the path of the config and checkpoint of vocoder. You can download the pretrain model of ``waveflow`` from [here](https://github.com/PaddlePaddle/Parakeet#vocoders).
+We currently support two vocoders, ``Griffin-Lim`` algorithm and ``WaveFlow``. You can set ``--vocoder`` to use one of them. If you want to use ``waveflow`` as your vocoder, you need to set ``--config_vocoder`` and ``--checkpoint_vocoder`` which are the path of the config and checkpoint of vocoder. You can download the pre-trained model of ``waveflow`` from [here](https://github.com/PaddlePaddle/Parakeet#vocoders).
 
 Or you can run the script file directly.
 
diff --git a/examples/fastspeech/synthesis.py b/examples/fastspeech/synthesis.py
index 96eceb5f062e7f06bd8db730774ded4d59a1bbfb..dde776ff7763aa69a7d29b4ab5017a3a234d37ce 100644
--- a/examples/fastspeech/synthesis.py
+++ b/examples/fastspeech/synthesis.py
@@ -39,8 +39,8 @@ def add_config_options_to_parser(parser):
     parser.add_argument(
         "--vocoder",
         type=str,
-        default="griffinlim",
-        choices=['griffinlim', 'waveflow'],
+        default="griffin-lim",
+        choices=['griffin-lim', 'waveflow'],
         help="vocoder method")
     parser.add_argument(
         "--config_vocoder", type=str, help="path of the vocoder config file")
@@ -53,11 +53,11 @@ def add_config_options_to_parser(parser):
     )
 
     parser.add_argument(
-        "--checkpoint", type=str, help="fastspeech checkpoint to synthesis")
+        "--checkpoint", type=str, help="fastspeech checkpoint for synthesis")
     parser.add_argument(
         "--checkpoint_vocoder",
         type=str,
-        help="vocoder checkpoint to synthesis")
+        help="vocoder checkpoint for synthesis")
 
     parser.add_argument(
         "--output",
@@ -96,7 +96,7 @@ def synthesis(text_input, args):
 
     _, mel_output_postnet = model(text, pos_text, alpha=args.alpha)
 
-    if args.vocoder == 'griffinlim':
+    if args.vocoder == 'griffin-lim':
         #synthesis use griffin-lim
         wav = synthesis_with_griffinlim(mel_output_postnet, cfg['audio'])
     elif args.vocoder == 'waveflow':
diff --git a/examples/fastspeech/synthesis.sh b/examples/fastspeech/synthesis.sh
index a94376f66b3cc345f8470bd3bf80f3f3251f4c5a..1ebed1bf57017969913a55e7c502731161a0d9c1 100644
--- a/examples/fastspeech/synthesis.sh
+++ b/examples/fastspeech/synthesis.sh
@@ -4,12 +4,12 @@ CUDA_VISIBLE_DEVICES=0 \
 python -u synthesis.py \
 --use_gpu=1 \
 --alpha=1.0 \
---checkpoint='./checkpoint/fastspeech/step-162000' \
---config='configs/ljspeech.yaml' \
+--checkpoint='./fastspeech_ljspeech_ckpt_1.0/fastspeech/step-162000' \
+--config='fastspeech_ljspeech_ckpt_1.0/ljspeech.yaml' \
 --output='./synthesis' \
 --vocoder='waveflow' \
---config_vocoder='../waveflow/checkpoint/waveflow_res128_ljspeech_ckpt_1.0/waveflow_ljspeech.yaml' \
---checkpoint_vocoder='../waveflow/checkpoint/waveflow_res128_ljspeech_ckpt_1.0/step-2000000' \
+--config_vocoder='./waveflow_res128_ljspeech_ckpt_1.0/waveflow_ljspeech.yaml' \
+--checkpoint_vocoder='./waveflow_res128_ljspeech_ckpt_1.0/step-2000000' \
 
 
 
diff --git a/examples/transformer_tts/README.md b/examples/transformer_tts/README.md
index b449c6ab6e8e5deb710425eee782bc6ba8b329b6..e8e013186f09e3608c8d397bc651ecc16eb8f5e9 100644
--- a/examples/transformer_tts/README.md
+++ b/examples/transformer_tts/README.md
@@ -95,10 +95,10 @@ python synthesis.py \
 --output=${OUTPUTPATH} \
 --config='configs/ljspeech.yaml' \
 --checkpoint_transformer=${CHECKPOINTPATH} \
---vocoder='griffinlim' \
+--vocoder='griffin-lim' \
 ```
 
-We currently support two vocoders, ``griffinlim`` and ``waveflow``. You can set ``--vocoder`` to use one of them. If you want to use ``waveflow`` as your vocoder, you need to set ``--config_vocoder`` and ``--checkpoint_vocoder`` which are the path of the config and checkpoint of vocoder. You can download the pretrain model of ``waveflow`` from [here](https://github.com/PaddlePaddle/Parakeet#vocoders).
+We currently support two vocoders,  ``Griffin-Lim`` algorithm and ``WaveFlow``. You can set ``--vocoder`` to use one of them. If you want to use ``waveflow`` as your vocoder, you need to set ``--config_vocoder`` and ``--checkpoint_vocoder`` which are the path of the config and checkpoint of vocoder. You can download the pre-trained model of ``waveflow`` from [here](https://github.com/PaddlePaddle/Parakeet#vocoders).
 
 Or you can run the script file directly.
 
diff --git a/examples/transformer_tts/synthesis.py b/examples/transformer_tts/synthesis.py
index 946463824f6bc354a8410ec8c373094251d5e8dc..effbffdc7a0cc21793a72eecd3ba39ead469ecce 100644
--- a/examples/transformer_tts/synthesis.py
+++ b/examples/transformer_tts/synthesis.py
@@ -49,19 +49,19 @@ def add_config_options_to_parser(parser):
     parser.add_argument(
         "--checkpoint_transformer",
         type=str,
-        help="transformer_tts checkpoint to synthesis")
+        help="transformer_tts checkpoint for synthesis")
     parser.add_argument(
         "--vocoder",
         type=str,
-        default="griffinlim",
-        choices=['griffinlim', 'waveflow'],
+        default="griffin-lim",
+        choices=['griffin-lim', 'waveflow'],
         help="vocoder method")
     parser.add_argument(
         "--config_vocoder", type=str, help="path of the vocoder config file")
     parser.add_argument(
         "--checkpoint_vocoder",
         type=str,
-        help="vocoder checkpoint to synthesis")
+        help="vocoder checkpoint for synthesis")
 
     parser.add_argument(
         "--output",
@@ -124,7 +124,7 @@ def synthesis(text_input, args):
                 i * 4 + j,
                 dataformats="HWC")
 
-    if args.vocoder == 'griffinlim':
+    if args.vocoder == 'griffin-lim':
         #synthesis use griffin-lim
         wav = synthesis_with_griffinlim(postnet_pred, cfg['audio'])
     elif args.vocoder == 'waveflow':
diff --git a/examples/transformer_tts/synthesis.sh b/examples/transformer_tts/synthesis.sh
index 1ceee837e0b5bd1db568de0ba7ff2b4348b53c8b..be91cd4441c6c0e0d63dedf547aa108551238e69 100644
--- a/examples/transformer_tts/synthesis.sh
+++ b/examples/transformer_tts/synthesis.sh
@@ -4,11 +4,11 @@ CUDA_VISIBLE_DEVICES=0 \
 python -u synthesis.py \
 --use_gpu=0 \
 --output='./synthesis' \
---config='configs/ljspeech.yaml' \
---checkpoint_transformer='./checkpoint/transformer/step-120000' \
+--config='transformer_tts_ljspeech_ckpt_1.0/ljspeech.yaml' \
+--checkpoint_transformer='./transformer_tts_ljspeech_ckpt_1.0/step-120000' \
 --vocoder='waveflow' \
---config_vocoder='../waveflow/checkpoint/waveflow_res128_ljspeech_ckpt_1.0/waveflow_ljspeech.yaml' \
---checkpoint_vocoder='../waveflow/checkpoint/waveflow_res128_ljspeech_ckpt_1.0/step-2000000' \
+--config_vocoder='./waveflow_res128_ljspeech_ckpt_1.0/waveflow_ljspeech.yaml' \
+--checkpoint_vocoder='./waveflow_res128_ljspeech_ckpt_1.0/step-2000000' \
 
 if [ $? -ne 0 ]; then
     echo "Failed in training!"