from datasets import load_dataset
# mind=load_dataset("PolyAI/minds14", name="en-AU", split="train")
from transformers import pipeline
pipe=pipeline("audio-classification",
              model="anton-l/xtreme_s_xlsr_300m_minds14"
             )
import gradio as gr
def classify_speech(file):
    pr=pipe(file)
    outputs={}
    for p in pr:
        outputs[p["label"]]=p["score"]
        return outputs
demo = gr.Interface(fn=classify_speech, inputs=gr.Audio(type='filepath'), outputs=gr.Label()
)
demo.launch(share=True)