app.py

import gradio as gr
from transformers import pipeline

# Load model
pipe = pipeline("audio-classification", model="ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition")

# Prediction function
def predict_emotion(audio):
    result = pipe(audio)
    return result[0]["label"].lower()

# Gradio Interface
interface = gr.Interface(
    fn=predict_emotion,
    inputs=gr.Audio(type="filepath", label="Upload Audio"),
    outputs=gr.Textbox(label="Predicted Emotion"),
    title="Audio Emotion Classifier"
)

# Launch
interface.launch()