Update app.py

app.py

@@ -32,22 +32,7 @@ from scipy.signal import butter, lfilter, wiener
 
 asr_model = pipeline("automatic-speech-recognition", model="cdactvm/w2v-bert-tamil_new")
 
-def createlex(filename):
-
-
-# Initialize an empty dictionary
-    data_dict = {}
 
-# Open the file and read it line by line
-    with open(filename, "r", encoding="utf-8") as f:
-        for line in f:
-        # Strip newline characters and split by tab
-            key, value = line.strip().split("\t")
-        # Add to dictionary
-            data_dict[key] = value
-    return data_dict
-    
-lex=createlex("num_words_ta.txt")
 # Function to apply a high-pass filter
 def high_pass_filter(audio, sr, cutoff=300):
     nyquist = 0.5 * sr
@@ -70,12 +55,28 @@ def apply_wiener_filter(audio):
 
 
 
+def createlex(filename):
+# Initialize an empty dictionary
+    data_dict = {}
+
+# Open the file and read it line by line
+    with open(filename, "r", encoding="utf-8") as f:
+        for line in f:
+        # Strip newline characters and split by tab
+            key, value = line.strip().split("\t")
+        # Add to dictionary
+            data_dict[key] = value
+    return data_dict
+    
+lex=createlex("num_words_ta.txt")
+
 def addnum(inlist):
     sum=0
     for num in inlist:
         sum+=int(num)
    
     return sum
+    
 from rapidfuzz import process
 def get_val(word, lexicon):
     threshold = 80  # Minimum similarity score