diff --git a/indextts/infer_v2.py b/indextts/infer_v2.py
index afc285a..b39090b 100644
--- a/indextts/infer_v2.py
+++ b/indextts/infer_v2.py
@@ -305,6 +305,22 @@ class IndexTTS2:
                 print(f"Audio too long ({audio.shape[1]} samples), truncating to {max_audio_samples} samples")
             audio = audio[:, :max_audio_samples]
         return audio, sr
+    
+    def normalize_emo_vec(self, emo_vector, apply_bias=True):
+        # apply biased emotion factors for better user experience,
+        # by de-emphasizing emotions that can cause strange results
+        if apply_bias:
+            # [happy, angry, sad, afraid, disgusted, melancholic, surprised, calm]
+            emo_bias = [0.9375, 0.875, 1.0, 1.0, 0.9375, 0.9375, 0.6875, 0.5625]
+            emo_vector = [vec * bias for vec, bias in zip(emo_vector, emo_bias)]
+
+        # the total emotion sum must be 0.8 or less
+        emo_sum = sum(emo_vector)
+        if emo_sum > 0.8:
+            scale_factor = 0.8 / emo_sum
+            emo_vector = [vec * scale_factor for vec in emo_vector]
+
+        return emo_vector
 
     # 原始推理模式
     def infer(self, spk_audio_prompt, text, output_path,
diff --git a/webui.py b/webui.py
index 302a5b3..0a97f75 100644
--- a/webui.py
+++ b/webui.py
@@ -6,8 +6,6 @@ import time
 
 import warnings
 
-import numpy as np
-
 warnings.filterwarnings("ignore", category=FutureWarning)
 warnings.filterwarnings("ignore", category=UserWarning)
 
@@ -104,14 +102,6 @@ with open("examples/cases.jsonl", "r", encoding="utf-8") as f:
                              example.get("emo_text") is not None]
                              )
 
-def normalize_emo_vec(emo_vec):
-    # emotion factors for better user experience
-    k_vec = [0.75,0.70,0.80,0.80,0.75,0.75,0.55,0.45]
-    tmp = np.array(k_vec) * np.array(emo_vec)
-    if np.sum(tmp) > 0.8:
-        tmp = tmp * 0.8/ np.sum(tmp)
-    return tmp.tolist()
-
 def gen_single(emo_control_method,prompt, text,
                emo_ref_path, emo_weight,
                vec1, vec2, vec3, vec4, vec5, vec6, vec7, vec8,
@@ -145,7 +135,7 @@ def gen_single(emo_control_method,prompt, text,
         pass
     if emo_control_method == 2:  # emotion from custom vectors
         vec = [vec1, vec2, vec3, vec4, vec5, vec6, vec7, vec8]
-        vec = normalize_emo_vec(vec)
+        vec = tts.normalize_emo_vec(vec, apply_bias=True)
     else:
         # don't use the emotion vector inputs for the other modes
         vec = None