plot descriptions

app.py

@@ -249,13 +249,13 @@ with gr.Blocks(css=css) as demo:
         with gr.Column(scale=7):
             piechart = gr.Plot()
         with gr.Column(scale=3):
-            gr.Markdown("The following pie chart shows the average probabilities of all emotions associated with the entire text.", elem_classes="info")
+            gr.Markdown("The chart gives an overview of the main emotions found in the text and how strongly each one is present.", elem_classes="info")
 
     with gr.Row():
         with gr.Column(scale=7):
             plot = gr.Plot()
         with gr.Column(scale=3):
-            gr.Markdown("The bar plot represents the relative frequency of emotion predictions at the sentence level.", elem_classes="info")
+            gr.Markdown("This bar chart shows how often each emotion appears in the sentences of the text.", elem_classes="info")
 
     with gr.Row():
         with gr.Column(scale=7):
@@ -265,13 +265,13 @@ with gr.Blocks(css=css) as demo:
                 wrap=True  # important
             )
         with gr.Column(scale=3):
-            gr.Markdown("The table displays the predicted emotion and its confidence value for each sentence in the text.", elem_classes="info")
+            gr.Markdown("This table shows the emotion detected in each sentence, along with how confident our prediction is.", elem_classes="info")
 
     with gr.Row():
         with gr.Column(scale=7):
             heatmap = gr.Plot()
         with gr.Column(scale=3):
-            gr.Markdown("The heatmap visualizes the probability of emotions within each sentence. The darker the color, the stronger the presence of the given emotion.", elem_classes="info")
+            gr.Markdown("This heatmap shows how strongly each emotion appears in every sentence. Darker colours mean stronger presence.", elem_classes="info")
 
     with gr.Row():
         model_info = gr.Markdown()