- Predicts next words as you type
- Real-time predictions
- Context-aware suggestions
- Confidence visualization
- One-click word insertion
What it does and key features
Built with
- R Shiny framework
- Natural Language Processing (NLP)
- Backoff modeling with smoothing
How the Model Works: Intelligent Backoff Architecture
Prediction Workflow: 
Key Techniques
- N-gram Modeling: Captures word sequence patterns
- Laplace Smoothing: Handles unseen words
- Context Prioritization: Uses highest available context
- Probability Scoring: Ranks suggestions by likelihood
Performance Summary: Accuracy Metrics
| Metric | Value |
|---|---|
| Top-1 Accuracy | 62% |
| Top-3 Accuracy | 78% |
| Response Time | <0.5s |
| Coverage | 92% of common phrases |
Performance Summary:Model Statistics
| Model | Count |
|---|---|
| Unigrams | 1,000 |
| Bigrams | 5,000 |
| Trigrams | 10,000 |
| Quadgrams | 15,000 |
Tested on 1,000 common phrases from blogs, news, and Twitter data
Using the Product: Seamless Prediction Experience
How to Use
- Type in the text box
- View color-coded suggestions
- Click to insert predictions
- Adjust suggestion count with slider
➡️ Live Demo: https://drsalmansaleem.shinyapps.io/next-word-predictor/
Future Enhancements: Next Development Phase
- Personalization based on user history
- Mobile app version (iOS/Android)
- Multi-language support
- Phrase completion feature
Potential Applications
- Accessibility tools
- Messaging apps
- Content creation assistants
- Language learning platforms
