Update app.py

app.py

@@ -18,18 +18,18 @@ def load_data(input_file):
     speech = librosa.resample(speech, sample_rate, 16000)
   return speech 
   
- def correct_casing(input_sentence):
-   sentences = nltk.sent_tokenize(input_sentence)
-   return (' '.join([s.replace(s[0],s[0].capitalize(),1) for s in sentences]))
+def correct_casing(input_sentence):
+  sentences = nltk.sent_tokenize(input_sentence)
+  return (' '.join([s.replace(s[0],s[0].capitalize(),1) for s in sentences]))
    
- def asr_transcript(input_file):
-   speech = load_data(input_file)
-   input_values = tokenizer(speech, return_tensors="pt").input_values
-   logits = model(input_values).logits
-   predicted_ids = torch.argmax(logits, dim=-1)
-   transcription = tokenizer.decode(predicted_ids[0])
-   transcription = correct_casing(transcription.lower())
-   return transcription
+def asr_transcript(input_file):
+  speech = load_data(input_file)
+  input_values = tokenizer(speech, return_tensors="pt").input_values
+  logits = model(input_values).logits
+  predicted_ids = torch.argmax(logits, dim=-1)
+  transcription = tokenizer.decode(predicted_ids[0])
+  transcription = correct_casing(transcription.lower())
+  return transcription
  
 
 gr.Interface(asr_transcript,