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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() |