app.py

app.py

@@ -0,0 +1,16 @@
+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()