markdown design for space

app.py

@@ -4,6 +4,7 @@ import csv
 import random
 import pandas as pd
 import gradio as gr
+from article import ARTICLE
 from utils import *
 import scipy.io.wavfile as wavf
 from huggingface_hub import Repository, upload_file
@@ -178,6 +179,23 @@ markdown = """<div style="text-align: center"><p style="font-size: 40px"> Africa
 This is a platform to contribute to your African language by recording your voice </div>"""
 
 
+markdown="""
+# 🌍 African Digits Recording Sprint
+
+> This is an event to record numbers (0-9) in your African language.
+
+1. Choose your African language
+2. Fill in the speaker metadata (age, gender, accent). This is optional but important to build better speech models.
+3. You will see the image of a number __(this is the number you will record)__.
+4. Fill in the word of that **number** (optional)
+5. Click record and say the number in your African language.
+6. Click ‘Submit’. It will save your record and go to the next number. 
+7. Repeat 1-7
+8. Leave a ❤ in the Space, if you found it fun.
+"""
+
+
+
 # Interface design begins
 block = gr.Blocks(css=BLOCK_CSS)
 with block:
@@ -192,7 +210,7 @@ with block:
                 accent = gr.inputs.Textbox(label="Accent (optional)",default='')  
 
             number = gr.Image('number/0.jpg',image_mode="L") 
-            text = gr.inputs.Textbox(placeholder='e.g. `one` is `otu` in Igbo or `ọkan` in Yoruba',label="Number in your language")
+            text = gr.inputs.Textbox(placeholder='e.g. `one` is `otu` in Igbo or `ọkan` in Yoruba',label="How is the number called in your language (optional)")
             record = gr.inputs.Audio(source="microphone",label='Record your voice')
             
             output_result = gr.outputs.HTML()
@@ -214,6 +232,6 @@ with block:
 
             #listen = gr.Button("Listen")
             listen_tab.select(display_records,inputs=[],outputs=display_html)
-            
+    gr.Markdown(ARTICLE)        
 
 block.launch()

article.py

@@ -0,0 +1,20 @@
+ARTICLE ="""
+**Motivation**
+
+In Africa, like in other continents of the world, people access vital information mainly through their mobile phones. Therefore the need for voice-enabled applications can be found in all sectors, from health, food to more fun (games, social media).
+
+Existing speech recognition services are not available in many African languages, and the speakers of these languages are excluded from the benefits of voice-enabled technologies. 
+
+This dataset will boost speech technologies (like speech-to-text, text-to-speech, speech translation, and modeling) for African languages, which hitherto had little or no public dataset. 
+
+**Note:** This is a continuous effort. the sprint is just to kick-start the event.
+
+**Benefits of such a dataset**
+- Useful dataset to introduce people to audio-related Machine Learning. It can be used as a simple training and/or evaluation dataset for speech processing tasks.
+
+**Contact**
+In case of questions, issues or anything contact Chris Emezue at:
+- [email protected] 
+
+
+""" 

data

@@ -1 +1 @@
-Subproject commit 29c4bca59acb2fb8f97049da5ba19069d175eceb
+Subproject commit f378d5cd72892211c6ff30dbecf891f953836e0f