diff --git a/inference.py b/inference.py
index 4121d5c..0f1b31d 100644
--- a/inference.py
+++ b/inference.py
@@ -1,9 +1,14 @@
-# loading json and creating model
+##Inference Script
+#importing modules
 from keras.models import model_from_json
 import keras
 import librosa
 import numpy as np
 from tensorflow.keras import optimizers
+import os
+import pandas as pd
+import librosa
+import glob 
 json_file = open('model.json', 'r')
 loaded_model_json = json_file.read()
 json_file.close()
@@ -12,14 +17,6 @@
 loaded_model.load_weights("saved_models/Emotion_Voice_Detection_Model.h5")
 print("Loaded model from disk")
 data, sampling_rate = librosa.load('output10.wav')
-import os
-import pandas as pd
-import librosa
-import glob 
-
-#plt.figure(figsize=(15, 5))
-#librosa.display.waveplot(data, sr=sampling_rate)
-#livedf= pd.DataFrame(columns=['feature'])
 X, sample_rate = librosa.load('Input4.m4a', res_type='kaiser_fast',duration=2.5,sr=22050*2,offset=0.5)
 sample_rate = np.array(sample_rate)
 mfccs = np.mean(librosa.feature.mfcc(y=X, sr=sample_rate, n_mfcc=13),axis=0)
@@ -34,6 +31,7 @@
                          verbose=1)
 livepreds1=livepreds.argmax(axis=1)
 liveabc = livepreds1.astype(int).flatten()
+#Labels assigned as per README of main repo.
 if liveabc == 0:
 	print("Female_angry")
 elif liveabc == 1: