Update app.py

app.py

@@ -5,15 +5,6 @@ import torch
 import gradio as gr
 from transformers import Wav2Vec2Tokenizer, Wav2Vec2ForCTC
 nltk.download("punkt")
-  
-  
-
-def correct_casing(input_sentence):
-  """ This function is for correcting the casing of the generated transcribed text
-  """
-  sentences = nltk.sent_tokenize(input_sentence)
-  return (' '.join([s.replace(s[0],s[0].capitalize(),1) for s in sentences]))
-  
 
 
 def asr_transcript(audio_file, language):
@@ -22,9 +13,9 @@ def asr_transcript(audio_file, language):
     
     #Selecting the language and loading the model and the tokenizer
     if language == "English":
-        model_name = "facebook/wav2vec2-large-960h-lv60-self"
+        model = "facebook/wav2vec2-large-960h-lv60-self"
     elif language == "Russian":
-        model_name = "jonatasgrosman/wav2vec2-large-xlsr-53-russian"
+        model = "jonatasgrosman/wav2vec2-large-xlsr-53-russian"
     
     tokenizer = Wav2Vec2Tokenizer.from_pretrained(model)
     model = Wav2Vec2ForCTC.from_pretrained(model)