Update app.py

app.py

@@ -59,8 +59,34 @@ def classify_audio(audio_file):
 
   return dict(zip(categories, map(float, probs)))
 
-audio = gr.Audio(type="filepath", label="Upload Audio <=20 seconds")
+description = """
+# Emotion Recognition from Audio
+
+Welcome to the app that recognizes emotion from the audio!
+
+## Instructions:
+- Upload or record audio (no more than 20 seconds for now)
+- Wait for processing and prediction from the model.
+
+## Emotions the app recognizes:
+1) Anger 
+2) Disgust
+3) Fear
+4) Happiness
+5) Pleasant Surprise
+6) Sadness
+7) Neutral
+
+## About:
+This application is actually using a computer vision model (an adaptation of ResNet) for detection and the model
+has been trained on a relatively small dataset of 2,380 recordings from two actors saying phrases in different emotions. 
+
+For more information, visit this [Github repo](https://github.com/KyawHtetWin/issem-machine-learning/tree/main/audio_emotion_detector)
+"""
+
+audio = gr.Audio(type="filepath", label="Upload Audio")
 label = gr.Label()
+md = gr.Markdown(description)
 # Gradio Interface
-inf = gr.Interface(fn=classify_audio, inputs=audio, outputs=label)
-inf.launch()
+inf = gr.Interface(fn=classify_audio, inputs=audio, outputs=label, title="Emotion Recognition", description=md)
+inf.launch(share=True)