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import gradio as gr | |
from transformers import pipeline | |
# Initialize the pipeline with the specified model | |
pipe = pipeline(model="Lingalingeswaran/whisper-small-sinhala") | |
def transcribe(audio): | |
# Transcribe the audio file to text | |
text = pipe(audio)["text"] | |
return text | |
# Create the Gradio interface | |
iface = gr.Interface( | |
fn=transcribe, | |
inputs=gr.Audio(sources=["microphone", "upload"], type="filepath"), | |
outputs="text", | |
title="Whisper Small Sinhala", | |
description="Realtime demo for Sinhala speech recognition using a fine-tuned Whisper small model.", | |
) | |
# Launch the interface | |
if __name__ == "__main__": | |
iface.launch() | |