added a profanity checker (#173)

Author: okaditya84

Profanity Checker/ProfanityChecker.py

@@ -0,0 +1,114 @@
+import speech_recognition as sr
+import requests
+import nltk
+import csv
+from nltk.tokenize import word_tokenize
+from nltk.corpus import stopwords
+from nltk.stem import WordNetLemmatizer
+from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer
+import tkinter as tk
+from tkinter import filedialog
+
+nltk.download('wordnet')
+
+nltk.download('punkt')
+nltk.download('stopwords')
+
+# Initialize the recognizer
+r = sr.Recognizer()
+
+# Ask the user whether to record from the microphone or select a file
+root = tk.Tk()
+root.withdraw()
+mode = input("Enter 'mic' to record from microphone or 'file' to select a file: ")
+
+if mode == 'mic':
+    # Record audio from the user
+    with sr.Microphone() as source:
+        print("Say something!")
+        audio = r.listen(source)
+
+    # Use Google Speech Recognition to convert audio to text
+    try:
+        text = r.recognize_google(audio)
+        print("You said: " + text)
+
+    except sr.UnknownValueError:
+        print("Google Speech Recognition could not understand audio")
+    except sr.RequestError as e:
+        print("Could not request results from Google Speech Recognition service; {0}".format(e))
+
+elif mode == 'file':
+    # Select a file using a dialog box
+    file_path = filedialog.askopenfilename()
+    print("Selected file:", file_path)
+
+    # Convert audio file to audio data
+    with sr.AudioFile(file_path) as source:
+        audio = r.record(source)
+
+    # Use Google Speech Recognition to convert audio to text
+    try:
+        text = r.recognize_google(audio)
+        print("Transcription: " + text)
+        
+
+    except sr.UnknownValueError:
+        print("Google Speech Recognition could not understand audio")
+    except sr.RequestError as e:
+        print("Could not request results from Google Speech Recognition service; {0}".format(e))
+
+else:
+    print("Invalid mode selected.")
+
+    # Preprocess the text
+stop_words = set(stopwords.words('english'))
+lemmatizer = WordNetLemmatizer()
+tokens = word_tokenize(text)
+filtered_tokens = [lemmatizer.lemmatize(w.lower()) for w in tokens if not w.lower() in stop_words]
+filtered_text = ' '.join(filtered_tokens)
+
+# Check for profanity in the text using the API
+response = requests.get("https://www.purgomalum.com/service/json?text=" + filtered_text)
+result = response.json()
+
+if result['result'] == filtered_text:
+    print("No profanity detected!")
+else:
+    print("Profanity detected!")
+    print("Censored text: " + result['result'])
+
+# Analyze sentiment of the text using VADER
+analyzer = SentimentIntensityAnalyzer()
+sentiment_scores = analyzer.polarity_scores(text)
+
+# Print sentiment scores
+print("\nSentiment Scores:")
+for key, value in sentiment_scores.items():
+    print(key, ': ', value)
+
+# Print sentiment label based on compound score
+sentiment_label = ''
+if sentiment_scores['compound'] > 0.5:
+    sentiment_label = 'Very Positive'
+elif sentiment_scores['compound'] > 0:
+    sentiment_label = 'Positive'
+elif sentiment_scores['compound'] == 0:
+    sentiment_label = 'Neutral'
+elif sentiment_scores['compound'] < -0.5:
+    sentiment_label = 'Very Negative'
+else:
+    sentiment_label = 'Negative'
+
+print("\nSentiment Label: " + sentiment_label)
+
+# Write input and output to CSV file
+with open('profanitycheckeroutput.csv', 'a', newline='') as file:
+    writer = csv.writer(file)
+    #name the columns
+    writer.writerow(['Input Text', 'Filtered Text', 'Positive Score', 'Negative Score', 'Neutral Score', 'Compound Score', 'Sentiment Label'])
+    #write the data
+
+    
+    writer.writerow([text, filtered_text, sentiment_scores['pos'], sentiment_scores['neg'], sentiment_scores['neu'], sentiment_scores['compound'], sentiment_label])
+