moved info inside Record tab

app.py

@@ -248,6 +248,8 @@ markdown="""
 Existing speech recognition systems do not support ANY African languages, excluding African speakers from voice-enabled devices. Our voice is our identity!
 And so the goal of the project is to make a simple digits dataset for African languages through crowd-sourcing. You can easily teach a model to recognise numbers in your language using this dataset.
 
+"""
+record_markdown = """
 > Record numbers 0-9 in your African language.
 
 1. Fill in your email. This is completely optional. We need this to track your progress for the prize.
@@ -265,7 +267,6 @@ __Note:__  You should record all numbers shown till the end. It does not count i
 """
 
 
-
 PLOTS_FOR_GRADIO = []
 FUNCTIONS_FOR_GRADIO = []
 
@@ -274,10 +275,12 @@ FUNCTIONS_FOR_GRADIO = []
 block = gr.Blocks(css=BLOCK_CSS)
 with block:
     gr.Markdown(markdown)
-    email = gr.inputs.Textbox(placeholder='your email',label="Email (Your email is not made public. We need it to consider you for the prize.)",default='')  
     with gr.Tabs():
         
         with gr.TabItem('Record'):
+            gr.Markdown(record_markdown)
+            email = gr.inputs.Textbox(placeholder='your email',label="Email (Your email is not made public. We need it to consider you for the prize.)",default='')  
+
             with gr.Row():
                 
                 language = gr.inputs.Dropdown(choices = sorted([lang_.title() for lang_ in list(DEFAULT_LANGS.keys())]),label="Choose language",default="Choose language")
@@ -298,7 +301,7 @@ with block:
                 
             save.click(save_record, inputs=[language,text,record,number,age,gender,accent,state,current_number,country,email,done_recording],outputs=[output_result,number,state,current_number,done_recording,record])
 
-        with gr.TabItem('Dashboard') as listen_tab:
+        with gr.TabItem('Dataset') as listen_tab:
             
             gr.Markdown("Statistics on the recordings contributed. You can find the dataset <a href='https://huggingface.co/datasets/chrisjay/crowd-speech-africa' target='blank'>here</a>.")
             display_html =  gr.HTML("""<div style="color: green">
@@ -364,7 +367,7 @@ with block:
             #listen = gr.Button("Listen")
             listen_tab.select(show_records,inputs=[],outputs=[display_html,plot]+PLOTS_FOR_GRADIO)
         
-        with gr.TabItem('Test Model') as listen_tab:
+        with gr.TabItem('Hear') as listen_tab:
             # Dropdown to choose a language from any of the 6
             # When you choose, it will load the correponding model
             # And then one can record a voice and get the model prediction