updated article.

app.py

@@ -55,6 +55,8 @@ def save_record(language,text,record,number,age,gender,accent,number_history,cur
     speaker_metadata['gender'] = gender if gender!=GENDER[0] else ''
     speaker_metadata['age'] = age if age !='' else ''
     speaker_metadata['accent'] = accent if accent!='' else ''
+
+
     if not done_recording:
         if language!=None and language!='Choose language' and record is not None and number is not None:
             language = language.lower()
@@ -131,7 +133,7 @@ def save_record(language,text,record,number,age,gender,accent,number_history,cur
         output_string = "<div class='finished'>"+output+"</div>"
         next_number = 0 # the default number
         next_number_image = f'number/best.gif'    
-        return output_string,next_number_image,number_history,next_number,done_recording
+        return output_string,next_number_image,number_history,next_number,done_recording,default_record
 
 def display_records():
     repo.git_pull()
@@ -182,15 +184,15 @@ This is a platform to contribute to your African language by recording your voic
 markdown="""
 # 🌍 African Digits Recording Sprint
 
-> This is an event to record numbers (0-9) in your African language.
+> 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)
+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
+7. Repeat 4-7
 8. Leave a ❤ in the Space, if you found it fun.
 """
 

article.py

@@ -7,12 +7,21 @@ Existing speech recognition services are not available in many African languages
 
 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.
+**Note:** This is a continuous effort. This 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.
 
+**About the dataset**
+
+The data (metadat,text, and audio recording) are uploaded to [a public Hugging Face dataset](https://huggingface.co/datasets/chrisjay/crowd-speech-africa).
+
+We do not collect your name, address or other sensitive information.
+
+If for some reason you want to remove your entry, please reach out by email.
+
 **Contact**
+
 In case of questions, issues or anything contact Chris Emezue at:
 - chris@huggingface.co