diff --git a/indextts/infer_v2.py b/indextts/infer_v2.py
index b851055..4d53e99 100644
--- a/indextts/infer_v2.py
+++ b/indextts/infer_v2.py
@@ -614,11 +614,22 @@ class QwenEmotion:
             # TODO: the "低落" (melancholic) emotion will always be mapped to
             # "悲伤" (sad) by QwenEmotion's text analysis. it doesn't know the
             # difference between those emotions even if user writes exact words.
+            # SEE: `self.melancholic_words` for current workaround.
             "低落": "melancholic",
             "惊讶": "surprised",
             "自然": "calm",
         }
         self.desired_vector_order = ["高兴", "愤怒", "悲伤", "恐惧", "反感", "低落", "惊讶", "自然"]
+        self.melancholic_words = {
+            # emotion text phrases that will force QwenEmotion's "悲伤" (sad) detection
+            # to become "低落" (melancholic) instead, to fix limitations mentioned above.
+            "低落",
+            "melancholy",
+            "melancholic",
+            "depression",
+            "depressed",
+            "gloomy",
+        }
         self.max_score = 1.2
         self.min_score = 0.0
 
@@ -686,6 +697,15 @@ class QwenEmotion:
             }
             # print(">> dict result", content)
 
+        # workaround for QwenEmotion's inability to distinguish "悲伤" (sad) vs "低落" (melancholic).
+        # if we detect any of the IndexTTS "melancholic" words, we swap those vectors
+        # to encode the "sad" emotion as "melancholic" (instead of sadness).
+        text_input_lower = text_input.lower()
+        if any(word in text_input_lower for word in self.melancholic_words):
+            # print(">> before vec swap", content)
+            content["悲伤"], content["低落"] = content.get("低落", 0.0), content.get("悲伤", 0.0)
+            # print(">>  after vec swap", content)
+
         return self.convert(content)