Update DoubleWords.py FillerWords.py Silence.py

DoubleWords.py

@@ -20,7 +20,7 @@ doc = nlp(text)
 
 # Tokenization
 tokens = [token.text for token in doc]
-
+print("*****Analyze Repeted Words in you're Speech*****");
 for i in range(len(tokens)):
     if tokens[i] == tokens[i + 1]:
         print(f" You stuck in this word :{tokens[i]}");
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FillerWords.py

@@ -25,5 +25,5 @@ def wordcount(filename, listwords):
 
         print("Have not filler word")
 
-
-wordcount("momo.txt", ["Like","you know", "I mean" ,"okay" ,"so", "actually" ,"basically","right"])
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+print("********Analyze Filler Word in your Speech********");
+wordcount("momo.txt", ["Like", "I mean" ,"okay" ,"so", "actually" ,"basically","right"])
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Silence.py

@@ -6,6 +6,7 @@ from pydub.silence import split_on_silence
 sound = AudioSegment.from_wav("C:/Users/Janitha Akalanka/PycharmProjects/English.wav")
 chunks = split_on_silence(sound, min_silence_len=200, silence_thresh=sound.dBFS - 16, keep_silence=150)
 
+# Chunk Folder file Path
 chunk_folder_name = "C:/Users/Janitha Akalanka/PycharmProjects/splits_by_pauses"
 
 # create folder to store chunks
@@ -16,4 +17,7 @@ for i, audio_chunk in enumerate(chunks, start=1):
     chunk_file = os.path.join(chunk_folder_name, f"chunk{i}.wav")
     audio_chunk.export(chunk_file, format="wav", bitrate='192k')
 
+print("****** How many times User Silence in their Speech *****")
+
+# print count of silence
 print(str(len(chunks) - 1) + " : Silence/s found")
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