Update app.py

app.py

@@ -10,7 +10,6 @@ import random
 import classify
 from whisper.model import Whisper
 from whisper.tokenizer import get_tokenizer
-from speechbrain.pretrained.interfaces import foreign_class
 from transformers import AutoModelForSequenceClassification, pipeline, WhisperTokenizer, RobertaForSequenceClassification, RobertaTokenizer, AutoTokenizer
 
 
@@ -39,11 +38,7 @@ class_options = {
 
 pipe = pipeline("automatic-speech-recognition", model="openai/whisper-large")
 
-def classify_emotion(audio):
-    #### Emotion classification ####
-    emotion_classifier = foreign_class(source="speechbrain/emotion-recognition-wav2vec2-IEMOCAP", pymodule_file="custom_interface.py", classname="CustomEncoderWav2vec2Classifier")
-    out_prob, score, index, text_lab = emotion_classifier.classify_file(audio)
-    return  emo_dict[text_lab[0]]
+
 
 def slider_logic(slider):
     threshold = 0