create preprocess function

backend/IT18218640/keyword_spotting_service.py

@@ -31,4 +31,18 @@ class _Keyword_Spotting_Service:
         predicted_index = np.argmax(predictions)
         predicted_keyword = self._mappings[predicted_index]
 
-        return predicted_keyword
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+        return predicted_keyword
+
+    def preprocess(self, file_path, n_mfcc=13, n_fft=2048, hop_length=512):
+
+        # load audio file
+        signal, sr = librosa.load(file_path)
+
+        # ensure consistency in the audio file length
+        if len(signal) > NUM_SAMPLES_TO_CONSIDER:
+            signal = signal[:NUM_SAMPLES_TO_CONSIDER]
+
+        # extract MFCCs
+        MFCCs = librosa.feature.mfcc(signal, n_mfcc=n_mfcc, n_fft=n_fft, hop_length=hop_length)
+
+        return MFCCs.T
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