fix gradio text

app.py

@@ -1,18 +1,12 @@
 from __future__ import annotations
 
 import os
-import pathlib
-from typing import Any, Dict
 
 import gradio as gr
-import numpy as np
-import torch
 
-# from seamless_communication.inference import Translator
+import torch
 import torchaudio
 
-# from fairseq2.assets import InProcAssetMetadataProvider, asset_store
-from huggingface_hub import snapshot_download
 from transformers import (
     SeamlessM4TFeatureExtractor,
     SeamlessM4TTokenizer,
@@ -25,19 +19,23 @@ from lang_list import (
     S2ST_TARGET_LANGUAGE_NAMES,
     S2TT_TARGET_LANGUAGE_NAMES,
     T2ST_TARGET_LANGUAGE_NAMES,
-    # T2TT_TARGET_LANGUAGE_NAMES,
     TEXT_SOURCE_LANGUAGE_NAMES,
 )
 
 
 DESCRIPTION = """\
-# SeamlessM4T
+### **IndicSeamlessM4T: Speech-to-Text Translation for Indian Languages** 🎙️➡️📜  
+
+This Gradio demo showcases **IndicSeamlessM4T**, a fine-tuned **SeamlessM4T** model for **speech-to-text translation** across **13 Indian languages and English**. Trained on **BhasaAnuvaad**, the largest open-source speech translation dataset for Indian languages, it delivers **accurate and robust translations** across diverse linguistic and acoustic conditions.  
+
+🔗 **Model Checkpoint:** [ai4bharat/seamless-m4t-v2-large-stt](https://huggingface.co/ai4bharat/seamless-m4t-v2-large-stt)  
 
-[SeamlessM4T](https://github.com/facebookresearch/seamless_communication) is designed to provide high-quality
-translation, allowing people from different linguistic communities to communicate effortlessly through speech and text.
-This unified model enables multiple tasks like Speech-to-Speech (S2ST), Speech-to-Text (S2TT), Text-to-Speech (T2ST)
-translation and more, without relying on multiple separate models. The model is also in use on the
-[SeamlessM4T demo website](https://seamless.metademolab.com/m4t?utm_source=huggingface&utm_medium=web&utm_campaign=seamless&utm_content=m4tspace).
+#### **How to Use:**  
+1. **Upload or record** an audio clip in any supported Indian language.  
+2. Click **"Translate"** to generate the corresponding text in the target language.  
+3. View or copy the output for further use.  
+
+🚀 Try it out and experience seamless speech translation for Indian languages!
 """
 
 hf_token = os.getenv("HF_TOKEN")
@@ -206,9 +204,9 @@ with gr.Blocks() as demo_asr:
                     choices=ASR_TARGET_LANGUAGE_NAMES,
                     value=DEFAULT_TARGET_LANGUAGE,
                 )
-            btn = gr.Button("Translate")
+            btn = gr.Button("Transcribe")
         with gr.Column():
-            output_text = gr.Textbox(label="Translated text")
+            output_text = gr.Textbox(label="Transcribed text")
 
     gr.Examples(
         examples=[