Update app.py

app.py

@@ -16,8 +16,8 @@ def predict(speech):
    audio_classifier = pipeline(
    task="audio-classification", model="ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition")
    preds = audio_classifier(audio_file)
-   preds = [{"score": round(pred["score"], 4), "label": pred["label"]} for pred in preds]
-   return preds
+   return [{"score": round(pred["score"], 4), "label": pred["label"]} for pred in preds]
+ 
    
 demo = gr.Interface(fn=predict, inputs='texts'  outputs="texts")