Create app.py

app.py

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+import gradio as gr
+from googletrans import Translator
+import torch
+# Initialize Translator
+from transformers import pipeline
+translator = Translator()
+MODEL_NAME = "openai/whisper-base"
+device = 0 if torch.cuda.is_available() else "cpu"
+pipe = pipeline(
+    task="automatic-speech-recognition",
+    model=MODEL_NAME,
+    chunk_length_s=30,
+    device=device,
+)
+
+
+def transcribe_audio(audio):
+   text = pipe(audio)["text"]
+   return text
+    # return translated_text
+
+audio_record = gr.inputs.Audio(source='microphone', label='Record Audio')
+output_text = gr.outputs.Textbox(label='Transcription')
+
+interface = gr.Interface(fn=transcribe_audio, inputs=audio_record, outputs=output_text)
+interface.launch()