speech2text_app.py

import torch
from transformers import pipeline
import gradio as gr

 # Function to transcribe audio using the OpenAI Whisper model
def transcript_audio(audio_file):
     # Initialize the speech recognition pipeline
     pipe = pipeline(
         "automatic-speech-recognition",
         model="openai/whisper-tiny.en",
         chunk_length_s=30,
     )
     # Transcribe the audio file and return the result
     result = pipe(audio_file, batch_size=8)["text"]
     return result

 # Set up Gradio interface
audio_input = gr.Audio(sources="upload", type="filepath")  # Audio input
output_text = gr.Textbox()  # Text output

 # Create the Gradio interface with the function, inputs, and outputs
iface = gr.Interface(fn=transcript_audio, 
                      inputs=audio_input, outputs=output_text, 
                      title="Audio Transcription App",
                      description="Upload the audio file")

 # Launch the Gradio app
iface.launch(server_name="0.0.0.0", server_port=7860)