diff --git a/convlab/policy/ussT5/emowoz_evaluate.py b/convlab/policy/ussT5/emowoz_evaluate.py
index 30ead5be5ee174b4659452ee65ff7af88065dd64..01cae7a82fa1c6c43c25b9ce01d1f2f5f8ae4029 100644
--- a/convlab/policy/ussT5/emowoz_evaluate.py
+++ b/convlab/policy/ussT5/emowoz_evaluate.py
@@ -65,21 +65,21 @@ def generate_result(model_checkpoint, data, stop=-1):
     for input_text, target_text in tqdm(zip(data["input_text"], data["target_text"]), ascii=True):
         if stop > 0 and i > stop:
             break
+        i += 1
+        inputs = tokenizer([input_text], return_tensors="pt", padding=True)
+        output = model.generate(input_ids=inputs["input_ids"],
+                                attention_mask=inputs["attention_mask"],
+                                do_sample=False)
+        output = tokenizer.batch_decode(
+            output, skip_special_tokens=True)[0]
+        if len(output) > 1:
+            print(output)
+            output = "illegal"
         if "satisfaction score" in input_text:
-            i += 1
-            inputs = tokenizer([input_text], return_tensors="pt", padding=True)
-            output = model.generate(input_ids=inputs["input_ids"],
-                                    attention_mask=inputs["attention_mask"],
-                                    do_sample=False)
-            output = tokenizer.batch_decode(
-                output, skip_special_tokens=True)[0]
-            if len(output) > 1:
-                print(output)
-                output = "illegal"
-
-            results.append({"input_text": input_text,
-                            "preds": tri_convert(output),
-                            "label": target_text})
+            output = tri_convert(output)
+        results.append({"input_text": input_text,
+                        "preds": output,
+                        "label": target_text})
     json.dump(results, open(os.path.join(
         model_checkpoint, "emowoz_result.json"), 'w'))
     return results
@@ -89,8 +89,9 @@ def read_result(result):
     preds = []
     label = []
     for r in result:
-        preds.append(r["preds"])
-        label.append(r["label"])
+        if "satisfaction score" in r["input_text"]:
+            preds.append(r["preds"])
+            label.append(r["label"])
     return preds, label