diff --git a/locales/en.yml b/locales/en.yml
index e2bbc7f3..93f07195 100644
--- a/locales/en.yml
+++ b/locales/en.yml
@@ -195,14 +195,8 @@ config_window:
   whisper_weight_type:
     label: Select Whisper Model
     desc: Generally, models with larger capacity tend to have higher accuracy, but this also results in longer transcription times and increased CPU usage. Please refer to the documentation for explanations of each model.
-    tiny: "tiny model (%{capacity})"
-    base: "base model (%{capacity}) (Recommended)"
-    small: "small model (%{capacity})"
-    medium: "medium model (%{capacity})"
-    large_v1: "large_v1 model (%{capacity})"
-    large_v2: "large_v2 model (%{capacity})"
-    large_v3: "large_v3 model (%{capacity})"
-
+    model_template: "%{model_name} model (%{capacity})"
+    recommended_model_template: "%{model_name} model (%{capacity}) (Recommended)"
 
   auto_clear_the_message_box:
     label: Auto Clear The Message Box
diff --git a/locales/ja.yml b/locales/ja.yml
index 7976e639..5d0b6acf 100644
--- a/locales/ja.yml
+++ b/locales/ja.yml
@@ -192,13 +192,8 @@ config_window:
   whisper_weight_type:
     label: Whisperモデルのタイプ
     desc: 基本的に、容量が多いモデルほど精度は高いですが、文字起こしまでの時間が伸び、CPU使用率も増加します。各モデルの説明はドキュメントをご覧ください。
-    tiny: "tiny モデル (%{capacity})"
-    base: "base モデル (%{capacity}) (推奨)"
-    small: "small モデル (%{capacity})"
-    medium: "medium モデル (%{capacity})"
-    large_v1: "large_v1 モデル (%{capacity})"
-    large_v2: "large_v2 モデル (%{capacity})"
-    large_v3: "large_v3 モデル (%{capacity})"
+    model_template: "%{model_name} モデル (%{capacity})"
+    recommended_model_template: "%{model_name} モデル (%{capacity}) (推奨)"
 
 
   auto_clear_the_message_box:
diff --git a/view.py b/view.py
index aac79d14..2d9b8fb0 100644
--- a/view.py
+++ b/view.py
@@ -952,14 +952,21 @@ class View():
 
     @staticmethod
     def getSelectableWhisperWeightTypeDict():
+        def callI18n(model_name, capacity, is_recommended=False):
+            if is_recommended is True:
+                return i18n.t("config_window.whisper_weight_type.recommended_model_template", model_name=model_name, capacity=capacity)
+            else:
+                return i18n.t("config_window.whisper_weight_type.model_template", model_name=model_name, capacity=capacity)
+
+        DICT_DATA = config.SELECTABLE_WHISPER_WEIGHT_TYPE_DICT
         return {
-            config.SELECTABLE_WHISPER_WEIGHT_TYPE_DICT["tiny"]: i18n.t("config_window.whisper_weight_type.tiny", capacity="74.5MB"),
-            config.SELECTABLE_WHISPER_WEIGHT_TYPE_DICT["base"]: i18n.t("config_window.whisper_weight_type.base", capacity="141MB"),
-            config.SELECTABLE_WHISPER_WEIGHT_TYPE_DICT["small"]: i18n.t("config_window.whisper_weight_type.small", capacity="463MB"),
-            config.SELECTABLE_WHISPER_WEIGHT_TYPE_DICT["medium"]: i18n.t("config_window.whisper_weight_type.medium", capacity="1.42GB"),
-            config.SELECTABLE_WHISPER_WEIGHT_TYPE_DICT["large-v1"]: i18n.t("config_window.whisper_weight_type.large_v1", capacity="2.87GB"),
-            config.SELECTABLE_WHISPER_WEIGHT_TYPE_DICT["large-v2"]: i18n.t("config_window.whisper_weight_type.large_v2", capacity="2.87GB"),
-            config.SELECTABLE_WHISPER_WEIGHT_TYPE_DICT["large-v3"]: i18n.t("config_window.whisper_weight_type.large_v3", capacity="2.87GB"),
+            DICT_DATA["tiny"]: callI18n("tiny", "74.5MB"),
+            DICT_DATA["base"]: callI18n("base", "141MB", True),
+            DICT_DATA["small"]: callI18n("small", "463MB"),
+            DICT_DATA["medium"]: callI18n("medium", "1.42GB"),
+            DICT_DATA["large-v1"]: callI18n("large-v1", "2.87GB"),
+            DICT_DATA["large-v2"]: callI18n("large-v2", "2.87GB"),
+            DICT_DATA["large-v3"]: callI18n("large-v3", "2.87GB"),
         }
 
 # Open Webpage Functions