• Typing on mobile is slow and error-prone
• Predictive text saves time and improves user experience
• Used by SwiftKey, Gboard and every modern keyboard

Goal: Build a fast and accurate next-word prediction app using NLP techniques on real-world English text data.

Training Data: HC Corpora (Blogs, News, Twitter)

• 150,000 lines sampled from 4 million lines of text

Algorithm: N-gram Backoff Model

1. Clean and tokenize input phrase
2. Match last 3 words in Quadgram table
3. Back off to last 2 words in Trigram table
4. Back off to last word in Bigram table
5. Return most frequent match at each level

Live at: https://bizsubba.shinyapps.io/nextword-app/

How to use:

• Type any phrase in the text box
• Click Predict Next Word button
• Top predicted word displayed instantly
• Top 5 candidate words shown in a table

Built with: R, Shiny, tidytext, dplyr, stringr

• Response time: less than 200ms
• Tested on 5 phrases: 5/5 predictions returned
• Model size: optimized for shinyapps.io

App URL: https://bizsubba.shinyapps.io/nextword-app/

Why this works:

• Trained on real Blogs, News and Twitter data
• Fast backoff model with no deep learning needed
• Clean simple interface anyone can use
• Easily extendable to other languages

Thank you!