app.py

import gradio as gr
from transformers import pipeline

# Load the Nigerian Accented English ASR model
transcriber = pipeline("automatic-speech-recognition", model="NCAIR1/NigerianAccentedEnglish")

def transcribe_audio(audio):
    """
    Transcribe audio file using the Nigerian Accented English model
    """
    if audio is None:
        return "Please upload an audio file."
    
    try:
        # Transcribe the audio
        result = transcriber(audio)
        return result["text"]
    except Exception as e:
        return f"Error: {str(e)}"

# Create Gradio interface
demo = gr.Interface(
    fn=transcribe_audio,
    inputs=gr.Audio(type="filepath", label="Upload Audio File"),
    outputs=gr.Textbox(label="Transcript"),
    title="Nigerian Accented English Transcription",
    description="Upload an audio file to get a transcript using the NCAIR1/NigerianAccentedEnglish model.",
    examples=[]
)

if __name__ == "__main__":
    demo.launch()