Next Word Predictor App

author: Capstone Project Pitch Deck date: 2026 autosize: true

Slide 1: Problem Statement & Objective

• Smart keyboards require fast and efficient next-word prediction to improve typing speeds on mobile and web devices.
• Challenge: High computational memory requirements for processing large text corpora in real-time.
• Goal: Develop a lightweight, accurate, and responsive text-prediction data product accessible via a web browser.

Slide 2: Data & Predictive Algorithm

• Dataset: Analysis of English text corpora collected from Twitter, Blogs, and News sources.
• Preprocessing: Tokenization, lowercasing, punctuation stripping, and whitespace removal.
• Algorithm: N-Gram Language Model utilizing a Backoff strategy (Trigram -> Bigram -> Unigram fallback) for speed and resource efficiency.

Slide 3: Shiny Application Interface

• User-friendly web interface designed with R Shiny.
• Key Features:
  • Fast single-word prediction based on user phrase input.
  • Interactive user experience with real-time reactive output.
  • Optimized lightweight .RData backend for minimal memory footprint and fast startup.

Slide 4: Experience & App Demonstration

• Simple 2-step user workflow:
  1. Type a multi-word English phrase into the input box.
  2. Click the prediction button to get the top predicted next word.
• Experience: Provides instantaneous results without lag or heavy browser memory consumption.

Slide 5: Business Pitch & Summary

• Value Proposition: Highly scalable prediction engine suitable for integration into messaging tools or smart input platforms.
• Future Roadmap: Expansion to multilingual models and deep learning/neural network integration.
• Access App: Experience the live application directly on Shinyapps.io!