updated

app.py

@@ -13,13 +13,13 @@ def emotion_predict(input):
   input_features = extract_feature(input, mfcc=True, chroma=True, mel=True, contrast=True, tonnetz=True)
   rf_prediction = classifier.predict(input_features.reshape(1,-1))
   if rf_prediction == 'happy':
-    return 'Happy 😎'
+    return 'kata-benda 😎'
   elif rf_prediction == 'neutral':
-    return 'Neutral 😐'
+    return 'kata-kerja 😐'
   elif rf_prediction == 'sad':
-    return 'Sad 😢'
+    return 'kata-sifat 😢'
   else:
-    return 'Angry 😤'
+    return 'kata-keterangan 😤'
   
 
 def plot_fig(input):
@@ -51,12 +51,12 @@ def plot_fig(input):
 with gr.Blocks() as app:
   gr.Markdown(
         """
-    # Speech Emotion Detector 🎵😍
-    This application classifies inputted audio 🔊 according to the verbal emotion into four categories:
-    1. Happy 😎
-    2. Neutral 😐
-    3. Sad 😢
-    4. Angry 😤
+     Speech Predict Detector 🎵😍
+    This application classifies inputted audio 🔊 according to the prediction into four categories:
+    1. kata-benda 😎
+    2. kata-kerja 😐
+    3. kata-sifat 😢
+    4. kata-keterangan 😤
     """
   )
   with gr.Tab("Record Audio"):