Update app.py

app.py

@@ -1,7 +1,30 @@
 import gradio as gr
+from transformers import RobertaTokenizerFast, TFRobertaForSequenceClassification, pipeline
+import whisper
 
-def greet(name):
-    return "Hello " + name + "!!"
+model = whisper.load_model('base')
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+tokenizer = RobertaTokenizerFast.from_pretrained("arpanghoshal/EmoRoBERTa")
+model2 = TFRobertaForSequenceClassification.from_pretrained("arpanghoshal/EmoRoBERTa")
+
+emotion = pipeline('sentiment-analysis', model='arpanghoshal/EmoRoBERTa')
+
+classifier = pipeline(task="text-classification", model="SamLowe/roberta-base-go_emotions", top_k=None)
+
+input_audio = gr.Audio(sources=['microphone','upload'], label='Speak with me...', show_label=True, interactive=True, format=['wav'])
+
+def voice_to_emotion(audio):
+    result = model.transcribe(audio, fp16 = False)
+    txt = result['text']
+    model_outputs = classifier(txt)
+    res = ''
+    for each in model_outputs[0]:
+        res = str(each['label'])
+    return res
+
+demo = gr.Interface(
+    fn=voice_to_emotion, 
+    inputs = input_audio,
+    outputs = "textbox")
+
+demo.launch()