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import gradio as gr | |
from transformers import pipeline | |
# Load the Whisper model for speech recognition | |
pipe = pipeline("automatic-speech-recognition", model="openai/whisper-small") | |
# Function to handle the speech recognition | |
def transcribe_audio(audio): | |
# Use the pipeline to transcribe the audio | |
result = pipe(audio)["text"] | |
return result | |
# Create a Gradio interface for the audio input and transcription output | |
interface = gr.Interface( | |
fn=transcribe_audio, # Function that handles the transcription | |
inputs=gr.Audio(source="microphone", type="filepath"), # Input as audio from mic | |
outputs="text", # Output as text | |
title="Whisper Speech Recognition", | |
description="Transcribe speech to text using OpenAI's Whisper model." | |
) | |
# Launch the Gradio interface | |
if __name__ == "__main__": | |
interface.launch() | |