metadata
title: README
emoji: 😻
colorFrom: yellow
colorTo: red
sdk: static
pinned: false
Tachygraphy Micro-text Analysis And Normalization
Tachygraphy Micro-text Analysis & Normalization
Welcome to the Tachygraphy Micro-text Analysis & Normalization Project. This page outlines our project’s key stages, sources, sample analysis examples, and team information.
Dashboard
Project Stages
- Sentiment Polarity Analysis
- Emotion Mood-tag Analysis
- Text Transformation & Normalization
- Stacked all 3 stages with their best models
- Data Correction & Collection
Sources & Deployment Links
| Training Source | Kaggle Collections | Hugging Face Org |
|---|---|---|
| GitHub @ Tachygraphy Micro-text Analysis & Normalization | Kaggle Dataset | Hugging Face @ Tachygraphy Micro-text Normalization |
| Deployment Source | Streamlit Deployment | Hugging Face Space Deployment |
|---|---|---|
| GitHub Deployment Repo | Streamlit App | Hugging Face Space |
Project Overview
Tachygraphy—originally developed to expedite writing—has evolved over centuries. In the 1990s, it reappeared as micro‑text, driving faster communication on social media with its “Anytime, Anyplace, Anybody, and Anything (4A)” characteristic. This project focuses on the analysis and normalization of micro‑text (the prevalent informal communication today) to improve NLP tasks such as sentiment analysis, emotion detection, and overall text transformation for clear 4A message decoding.