diff --git a/api.py b/api.py
index 754f0769..aa5df909 100644
--- a/api.py
+++ b/api.py
@@ -456,13 +456,14 @@ def handle_change(path, text, language):
 
     return JSONResponse({"code": 0, "message": "Success"}, status_code=200)
 
+def _empty_parameter(*items):
+    for item in items:
+        if item is None or item == "":
+            return True
+    return False
 
 def handle(refer_wav_path, prompt_text, prompt_language, text, text_language):
-    if (
-            refer_wav_path == "" or refer_wav_path is None
-            or prompt_text == "" or prompt_text is None
-            or prompt_language == "" or prompt_language is None
-    ):
+    if (_empty_parameter(refer_wav_path, prompt_text, prompt_language, text, text_language)):
         refer_wav_path, prompt_text, prompt_language = (
             default_refer.path,
             default_refer.text,
@@ -470,22 +471,26 @@ def handle(refer_wav_path, prompt_text, prompt_language, text, text_language):
         )
         if not default_refer.is_ready():
             return JSONResponse({"code": 400, "message": "未指定参考音频且接口无预设"}, status_code=400)
+        if _empty_parameter(text, text_language):
+            return JSONResponse({"code": 400, "message": "缺少参数: text 或 text_language"}, status_code=400)
+    try:
+        with torch.no_grad():
+            gen = get_tts_wav(
+                refer_wav_path, prompt_text, prompt_language, text, text_language
+            )
+            sampling_rate, audio_data = next(gen)
 
-    with torch.no_grad():
-        gen = get_tts_wav(
-            refer_wav_path, prompt_text, prompt_language, text, text_language
-        )
-        sampling_rate, audio_data = next(gen)
+        wav = BytesIO()
+        sf.write(wav, audio_data, sampling_rate, format="wav")
+        wav.seek(0)
 
-    wav = BytesIO()
-    sf.write(wav, audio_data, sampling_rate, format="wav")
-    wav.seek(0)
-
-    torch.cuda.empty_cache()
-    if device == "mps":
-        print('executed torch.mps.empty_cache()')
-        torch.mps.empty_cache()
-    return StreamingResponse(wav, media_type="audio/wav")
+        torch.cuda.empty_cache()
+        if device == "mps":
+            print('executed torch.mps.empty_cache()')
+            torch.mps.empty_cache()
+        return StreamingResponse(wav, media_type="audio/wav")
+    except Exception as e:
+        return JSONResponse({"code": 400, "message": f"error: {e}"}, status_code=400)
 
 
 app = FastAPI()