diff --git a/examples/aishell/s0/conf/augmentation.json b/examples/aishell/s0/conf/augmentation.json
index 5635d9c8..1987ad42 100644
--- a/examples/aishell/s0/conf/augmentation.json
+++ b/examples/aishell/s0/conf/augmentation.json
@@ -15,5 +15,20 @@
       "max_shift_ms": 5
     },
     "prob": 1.0
+  },
+  {
+    "type": "specaug",
+    "params": {
+      "F": 10,
+      "T": 50,
+      "n_freq_masks": 2,
+      "n_time_masks": 2,
+      "p": 1.0,
+      "W": 80,
+      "adaptive_number_ratio": 0,
+      "adaptive_size_ratio": 0,
+      "max_n_time_masks": 20
+    },
+    "prob": 1.0
   }
 ]
diff --git a/examples/aishell/s1/conf/chunk_conformer.yaml b/examples/aishell/s1/conf/chunk_conformer.yaml
index 8f67ef41..e8dabea5 100644
--- a/examples/aishell/s1/conf/chunk_conformer.yaml
+++ b/examples/aishell/s1/conf/chunk_conformer.yaml
@@ -93,7 +93,7 @@ training:
 
 
 decoding:
-  batch_size: 1
+  batch_size: 128
   error_rate_type: cer 
   decoding_method: attention # 'attention', 'ctc_greedy_search', 'ctc_prefix_beam_search', 'attention_rescoring'
   lang_model_path: data/lm/common_crawl_00.prune01111.trie.klm
@@ -104,11 +104,11 @@ decoding:
   cutoff_top_n: 0
   num_proc_bsearch: 8
   ctc_weight: 0.5 # ctc weight for attention rescoring decode mode.
-  decoding_chunk_size: 16 # decoding chunk size. Defaults to -1.
+  decoding_chunk_size: -1 # decoding chunk size. Defaults to -1.
       # <0: for decoding, use full chunk.
       # >0: for decoding, use fixed chunk size as set.
       # 0: used for training, it's prohibited here. 
   num_decoding_left_chunks: -1  # number of left chunks for decoding. Defaults to -1.
-  simulate_streaming: True  # simulate streaming inference. Defaults to False.
+  simulate_streaming: true  # simulate streaming inference. Defaults to False.
 
 
diff --git a/examples/librispeech/s1/conf/chunk_confermer.yaml b/examples/librispeech/s1/conf/chunk_confermer.yaml
index 0d07d0a7..ec945a18 100644
--- a/examples/librispeech/s1/conf/chunk_confermer.yaml
+++ b/examples/librispeech/s1/conf/chunk_confermer.yaml
@@ -56,7 +56,7 @@ model:
         pos_enc_layer_type: 'rel_pos'
         selfattention_layer_type: 'rel_selfattn'
         causal: True
-        use_dynamic_chunk: True
+        use_dynamic_chunk: true
         cnn_module_norm: 'layer_norm' # using nn.LayerNorm makes model converge faster
         use_dynamic_left_chunk: false
 
@@ -110,6 +110,6 @@ decoding:
       # >0: for decoding, use fixed chunk size as set.
       # 0: used for training, it's prohibited here. 
   num_decoding_left_chunks: -1  # number of left chunks for decoding. Defaults to -1.
-  simulate_streaming: False  # simulate streaming inference. Defaults to False.
+  simulate_streaming: true  # simulate streaming inference. Defaults to False.