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This program checks for any abusive words and does sentiment analysis of an audio file.

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Profanity-Checker

This repository contains a Python script that performs profanity checking and sentiment analysis on audio files. The script utilizes APIs from Google Speech Recognition, Purgomalum, and the VADER Sentiment Analysis tool.

Features

  • Record audio from the microphone or select an audio file for analysis
  • Perform profanity checking using the Purgomalum API
  • Analyze sentiment using the VADER Sentiment Analysis tool
  • Generate sentiment scores and labels
  • Store input and output data in a CSV file

Installation

  1. Clone the repository:

    git clone https://github.com/okaditya84/Profanity-Checker.git
    
    
  2. Install the required dependencies by running the following command:

    pip install -r requirements.txt
    
    
  3. Ensure you have the necessary API keys:

  • Google Speech Recognition API key (follow Google's documentation on obtaining an API key)
  • Purgomalum API key (visit the Purgomalum website and sign up to get an API key)

Usage

  1. Run the Profanity checker.py script:
    python Profanity\ checker.py
    
  2. Choose the desired mode of input:
  • Enter 'mic' to record audio from the microphone.
  • Enter 'file' to select an audio file for analysis.
  1. Follow the on-screen instructions:
  • If using the microphone, speak clearly into the microphone after the prompt.
  • If selecting a file, use the file dialog to choose an audio file.
  1. Wait for the script to perform the following tasks:
  • Convert audio to text using Google Speech Recognition.
  • Preprocess the text by removing stop words and lemmatizing words.
  • Check for profanity in the text using the Purgomalum API.
  • Analyze the sentiment of the text using VADER Sentiment Analysis.
  • Display the results, including the sentiment scores and label.
  1. The input text, filtered text, sentiment scores, and sentiment label will be saved in the 'output.csv' file.

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This program checks for any abusive words and does sentiment analysis of an audio file.

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