Project
AI Humanizer — Human vs AI Content Detection System
Year
2025
Service
NLP
AI Humanizer
Project Overview
This project is an AI-powered content detection system built on fine-tuned transformer models such as RoBERTa, trained using the HC3 (Human ChatGPT Comparison Corpus) dataset. It provides a modular pipeline for data validation, preprocessing, training, and inference, along with a simple web interface that allows users to paste text and instantly receive classification results.
Project Overview
This project is an AI-powered content detection system built on fine-tuned transformer models such as RoBERTa, trained using the HC3 (Human ChatGPT Comparison Corpus) dataset. It provides a modular pipeline for data validation, preprocessing, training, and inference, along with a simple web interface that allows users to paste text and instantly receive classification results.
The Problem
The rapid growth of large language models has made it increasingly difficult to distinguish between human-written and AI-generated content. This creates challenges in academic integrity, content authenticity, misinformation control, and digital trust. Existing methods often lack accuracy, transparency, or real-time usability, limiting their effectiveness in practical scenarios.
The Problem
The rapid growth of large language models has made it increasingly difficult to distinguish between human-written and AI-generated content. This creates challenges in academic integrity, content authenticity, misinformation control, and digital trust. Existing methods often lack accuracy, transparency, or real-time usability, limiting their effectiveness in practical scenarios.
The Solution
AI Humanizer applies a fine-tuned transformer-based classifier to analyze linguistic patterns, contextual structure, and semantic consistency within text. The system follows a modular ML pipeline that ensures reliable data handling, secure model storage, and reproducible training, while offering a user-friendly interface for instant, real-time content verification.
The Solution
AI Humanizer applies a fine-tuned transformer-based classifier to analyze linguistic patterns, contextual structure, and semantic consistency within text. The system follows a modular ML pipeline that ensures reliable data handling, secure model storage, and reproducible training, while offering a user-friendly interface for instant, real-time content verification.
The Result
The platform delivers accurate and fast classification of human versus AI-generated text, improving trust and authenticity in digital content. It enables educators, publishers, and users to verify content reliability, supports scalable deployment, and provides a foundation for future extensions such as AI model attribution and hybrid text detection.
The Result
The platform delivers accurate and fast classification of human versus AI-generated text, improving trust and authenticity in digital content. It enables educators, publishers, and users to verify content reliability, supports scalable deployment, and provides a foundation for future extensions such as AI model attribution and hybrid text detection.
