Next Word Prediction: Back-off Model

Dhruv
January 2026

Slide 1: How the Model Works

The engine uses a Back-off algorithm for real-time prediction.

  • Tokenization: Input is cleaned (lowercased/punctuation removed).
  • N-gram Hierarchy: 1. Quadgrams: Uses last 3 words to find a 4th.
    1. Trigrams: Backs off to last 2 words if no quadgram match.
    2. Bigrams: Backs off to the last word.
  • Efficiency: Instant results via pre-indexed frequency tables.

Slide 2: Quantitative Performance

Performance is measured by Accuracy and Inference Speed.

  • Accuracy: High hit rate for common English phrases using a massive corpus.
  • Latency: Average prediction time is < 10ms, perfect for mobile.

plot of chunk unnamed-chunk-1

Slide 3: The Shiny Application

The application provides a seamless “type-and-see” experience.

  • Real-time Prediction: As you type in the text box, the model reacts instantly.
  • Clean UI: Designed with a focus on simplicity and speed.
  • Fallback Logic: If a unique phrase is typed, the model defaults to “the”.

Live Demo

dhruv-dscapstone.shinyapps.io

The app is lightweight and optimized for both desktop and mobile browsers.

Slide 4: User Guide & Impact

How to Use the App

  1. Input: Enter a partial sentence (e.g., “a case of”).
  2. Output: The predicted next word appears immediately below the input.
  3. Completion: Use the predicted word to complete your thought faster.

Business Impact

This tool reduces manual typing effort and improves data entry speed. By leveraging the Stupid Back-off algorithm, we achieve the perfect balance between linguistic accuracy and the extreme speed required for a modern web interface.