update

app.py

@@ -163,13 +163,13 @@ demo = gr.Blocks()
 with demo:
   gr.Markdown("<h1><center>Talk to Your Multilingual AI Assistant</center></h1>")
   gr.Markdown(
-        """Model pipeline consisting of - <br>- [**Whisper**](https://github.com/openai/whisper)for Speech-to-text, <br>- [**Bloom**](https://huggingface.co/bigscience/bloom) for Text-generation, and <br>- [**CoquiTTS**](https://huggingface.co/coqui) for Text-To-Speech. <br><br> Front end is built using [**Gradio Block API**](https://gradio.app/docs/#blocks).<br>All three models are Multilingual, however, there are only these three overlapping languages among them - Spanish (es), French(fr), and English(en). Hence it would be suggested to test using these languages to get the best results out of this ML-App. If an English voice input is given then both the textbox on the left-hand side would show the same transcripts. However, if the input is either in Spanish or French, then the first textbox would show the language transcript, while the next one would show its English translations.
+        """Model pipeline consisting of - <br>- [**Whisper**](https://github.com/openai/whisper)for Speech-to-text, <br>- [**Bloom**](https://huggingface.co/bigscience/bloom) for Text-generation, and <br>- [**CoquiTTS**](https://huggingface.co/coqui) for Text-To-Speech. <br><br> Front end is built using [**Gradio Block API**](https://gradio.app/docs/#blocks).<br>All three models are Multilingual, however, there are only these three overlapping languages among them - Spanish (es), French(fr), and English(en). Hence it would be suggested to test using these languages to get the best results out of this ML-App. If an English voice input is given then both the textbox on the left-hand side would show the same transcripts. However, if the input is either in _Spanish_ or _French_, then the first textbox would show the language transcript, while the next one would show its English translations.
         """)
   with gr.Row():
     with gr.Column():
-      in_audio = gr.Audio(source="microphone",  type="filepath", label='Record your voice here')  #type='filepath'
+      in_audio = gr.Audio(source="microphone",  type="filepath", label='Record your voice here in English, Spanish or French for best results-')  #type='filepath'
       b1 = gr.Button("AI response pipeline (Whisper - Bloom - Coqui pipeline)")
-      out_transcript = gr.Textbox(label= 'As is Transcript using OpenAI Whisper')
+      out_transcript = gr.Textbox(label= 'English/Spanish/French Transcript of your Audio using OpenAI Whisper')
       out_translation_en = gr.Textbox(label= 'English Translation of audio using OpenAI Whisper')
     with gr.Column():
       out_audio = gr.Audio(label='AI response in Audio form in your preferred language')