initial commit

app.py

@@ -12,14 +12,14 @@ classifier = pickle.load(open('finalized_rf.sav', 'rb'))
 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 == 'kata_benda':
-    return 'kata_benda'
-  elif rf_prediction == 'kata_kerja':
-    return 'kata_kerja'
-  elif rf_prediction == 'kata_keterangan':
-    return 'kata_keterangan'      
+  if rf_prediction == 'kata-benda':
+    return 'kata-benda'
+  elif rf_prediction == 'kata-kerja':
+    return 'kata-kerja'
+  elif rf_prediction == 'kata-keterangan':
+    return 'kata-keterangan'      
   else:
-    return 'kata_sifat'
+    return 'kata-sifat'
   
 
 def plot_fig(input):
@@ -51,12 +51,13 @@ def plot_fig(input):
 with gr.Blocks() as app:
   gr.Markdown(
         """
-    # PROLOVE 🎵
-    This application classifies inputted audio 🔊 according to pronunciation into four categories:
-    1. kata_benda 
-    2. kata_kerja 
-    3. kata_keterangan 
-    4. kata_sifat 
+    #  💞PROLOVE 🎵🎸🎼
+    
+    This application classifies inputted audio according to pronunciation into four categories:
+    1. kata benda 
+    2. kata kerja 
+    3. kata keterangan 
+    4. kata sifat 
     """
   )
   with gr.Tab("Record Audio"):
@@ -71,8 +72,8 @@ with gr.Blocks() as app:
       plot_record = gr.Button("Display Audio Signal")
       plot_record_c = gr.Plot(label='Waveform Of the Audio')
     
-    record_button = gr.Button("Detect Emotion")
-    record_output = gr.Text(label = 'Emotion Detected')
+    record_button = gr.Button("Detect vocabulary")
+    record_output = gr.Text(label = 'result')
 
   with gr.Tab("Upload Audio File"):
     gr.Markdown(
@@ -92,8 +93,8 @@ with gr.Blocks() as app:
       plot_upload = gr.Button("Display Audio Signal")
       plot_upload_c = gr.Plot(label='Waveform Of the Audio')
 
-    upload_button = gr.Button("Detect Emotion")
-    upload_output = gr.Text(label = 'Emotion Detected')
+    upload_button = gr.Button("Detect vocabulary")
+    upload_output = gr.Text(label = 'result')
     
   record_button.click(emotion_predict, inputs=record_input, outputs=record_output)
   upload_button.click(emotion_predict, inputs=upload_input, outputs=upload_output)