Welcome to the Faulty Text AS Center repository! We are a team of researchers dedicated to exploring the fascinating world of text restoration, with a unique focus on deciphering and recovering intentionally distorted Korean text. Our project is not just a playful experiment—it is a dive into the intersection of natural language processing (NLP), cultural nuances, and computational creativity.

In the era of globalized communication, automated content moderation systems often struggle to understand the intricacies of regional languages and cultural contexts. For example, many reviews and comments in Korean are modified in ways that make them difficult to translate or understand, often to bypass moderation. While these distorted texts are incomprehensible to non-Korean speakers, they convey meaning to native speakers through subtle contextual or phonetic clues.

Our research aims to:

• Develop algorithms capable of reconstructing these "faulty" or intentionally modified Korean texts.
• Preserve the cultural and linguistic subtleties embedded in such texts.
• Enhance the performance of NLP systems in handling non-standard language inputs.

• Innovative Text Restoration: Algorithms tailored to handle distorted Korean text, including phonetic modifications, character replacements, and contextual ambiguities.
• Cultural Awareness: Solutions that respect and understand the unique patterns of Korean internet slang and linguistic creativity.
• Applications in NLP: Potential integration with machine translation, sentiment analysis, and content moderation systems.

Our primary goal is to contribute to the development of smarter and culturally aware NLP systems by addressing the challenges posed by distorted Korean text. By doing so, we aim to:

1. Make digital communication more inclusive and accessible.
2. Support the linguistic and cultural richness of Korean in the global tech landscape.
3. Provide tools for researchers and developers working with complex and nuanced languages.

• Sunjun Hwang
  • site
  • Competencies
    • Python (NumPy, Pandas, matplotlib, Torch, etc.)
    • Full-Stack developer
    • Undergraduate researcher in Yonsei University
  • Research Areas
    • NLP
    • Quantum computing
    • Highly reliable artificial intelligence
    • Computer structure and microprocessors
• Eunseok Lee
  • Competencies
    • Python (Torch), SQL
    • Data scientists
  • Key Research
    • Statistics
    • Linear Regression
    • Data Sampling
    • Applied Probability Modeling
    • Artificial Intelligence Based Optimization and DeepLearning
• Younghoon Kim
• Jiwon Kim