diff --git a/basics/base_task.py b/basics/base_task.py
index 059440bdb..4e3af855c 100644
--- a/basics/base_task.py
+++ b/basics/base_task.py
@@ -88,16 +88,40 @@ def setup(self, stage):
         self.phone_encoder = self.build_phone_encoder()
         self.model = self.build_model()
         # utils.load_warp(self)
+        self.unfreeze_all_params()
+        if hparams['freezing_enabled']:
+            self.freeze_params()
         if hparams['finetune_enabled'] and get_latest_checkpoint_path(pathlib.Path(hparams['work_dir'])) is None:
-            self.load_finetune_ckpt( self.load_pre_train_model())
+            self.load_finetune_ckpt(self.load_pre_train_model())
         self.print_arch()
         self.build_losses()
         self.train_dataset = self.dataset_cls(hparams['train_set_name'])
         self.valid_dataset = self.dataset_cls(hparams['valid_set_name'])
 
+    def get_need_freeze_state_dict_key(self, model_state_dict) -> list:
+        key_list = []
+        for i in hparams['frozen_params']:
+            for j in model_state_dict:
+                if j.startswith(i):
+                    key_list.append(j)
+        return list(set(key_list))
+
+    def freeze_params(self) -> None:
+        model_state_dict = self.state_dict().keys()
+        freeze_key = self.get_need_freeze_state_dict_key(model_state_dict=model_state_dict)
+
+        for i in freeze_key:
+            params=self.get_parameter(i)
+
+            params.requires_grad = False
+
+    def unfreeze_all_params(self) -> None:
+        for i in self.model.parameters():
+            i.requires_grad = True
+
     def load_finetune_ckpt(
             self, state_dict
-    ):
+    ) -> None:
 
         adapt_shapes = hparams['finetune_strict_shapes']
         if not adapt_shapes:
@@ -276,7 +300,7 @@ def build_optimizer(self, model):
             optimizer_args['betas'] = (optimizer_args['beta1'], optimizer_args['beta2'])
         optimizer = build_object_from_config(
             optimizer_args['optimizer_cls'],
-            filter(lambda p: p.requires_grad, model.parameters()),
+            model.parameters(),
             **optimizer_args
         )
         return optimizer
diff --git a/configs/acoustic.yaml b/configs/acoustic.yaml
index 368a7b5af..88ae1b12b 100644
--- a/configs/acoustic.yaml
+++ b/configs/acoustic.yaml
@@ -102,3 +102,6 @@ finetune_ignored_params:
   - model.fs2.txt_embed
   - model.fs2.spk_embed
 finetune_strict_shapes: true
+
+freezing_enabled: false
+frozen_params: []
diff --git a/configs/base.yaml b/configs/base.yaml
index bc570e46a..4561b3325 100644
--- a/configs/base.yaml
+++ b/configs/base.yaml
@@ -100,3 +100,6 @@ finetune_ignored_params: []
 
 
 finetune_strict_shapes: true
+
+freezing_enabled: false
+frozen_params: []
diff --git a/configs/variance.yaml b/configs/variance.yaml
index d4dc91a3b..b23c2a5a8 100644
--- a/configs/variance.yaml
+++ b/configs/variance.yaml
@@ -111,3 +111,6 @@ finetune_ignored_params:
   - model.fs2.txt_embed
   - model.fs2.encoder.embed_tokens
 finetune_strict_shapes: true
+
+freezing_enabled: false
+frozen_params: []
diff --git a/docs/ConfigurationSchemas.md b/docs/ConfigurationSchemas.md
index 417350a45..b37423400 100644
--- a/docs/ConfigurationSchemas.md
+++ b/docs/ConfigurationSchemas.md
@@ -1422,6 +1422,54 @@ int
 
 16000
 
+### freezing_enabled
+
+Whether enabling parameter freezing during training.
+
+#### visibility
+
+all
+
+#### scope
+
+training
+
+#### customizability
+
+normal
+
+#### type
+
+bool
+
+#### default
+
+False
+
+### frozen_params
+
+Parameter name prefixes to freeze during training.
+
+#### visibility
+
+all
+
+#### scope
+
+training
+
+#### customizability
+
+normal
+
+#### type
+
+list
+
+#### default
+
+[]
+
 ### fmin
 
 Minimum frequency of mel extraction.
@@ -3416,4 +3464,3 @@ int
 
 2048
 
-