Swipe Typing Technical Specification
Overview
Neural swipe typing uses an ONNX transformer model with beam search to predict words from gesture paths.
Key Components
| Component | File | Purpose |
|---|
| Trajectory Processor | SwipeTrajectoryProcessor.kt | Convert touch points to key sequence |
| Neural Engine | NeuralPredictionEngine.kt | ONNX model inference |
| Beam Search | BeamSearchDecoder.kt | Find top-k word predictions |
| Vocabulary | OptimizedVocabulary.kt | Dictionary and trie lookup |
| Keyboard Grid | KeyboardGrid.kt | Map coordinates to keys |
Architecture
Touch Events (Pointers.kt)
↓
SwipeTrajectoryProcessor
↓ (key sequence)
NeuralPredictionEngine
↓ (token probabilities)
BeamSearchDecoder
↓ (top-k candidates)
SuggestionHandler → UI
Neural Model
| Property | Value |
|---|
| Format | ONNX Runtime Mobile |
| Architecture | Transformer encoder |
| Input | Key token sequence |
| Output | Probability distribution over vocabulary |
| Size | ~2 MB per language |
Beam Search Configuration
From Config.kt:
| Setting | Key | Default | Range | Source |
|---|
| Beam Width | neural_beam_width | 6 | 1-32 | Config.kt:130, validator backup/SettingsValidation.kt |
| Max Length | neural_max_length | 20 | 10-50 | Config.kt (NEURAL_MAX_LENGTH) |
| Confidence Threshold | neural_confidence_threshold | 0.01 | 0.0-1.0 | Config.kt:132 (NEURAL_CONFIDENCE_THRESHOLD) |
| ONNX Models | bundled assets | — | — | src/main/assets/models/swipe_{encoder,decoder}_android.onnx |
Key Methods
SwipeTrajectoryProcessor.kt
// Line ~120: Convert swipe to tokens
fun processTrajectory(points: List<TouchPoint>): List<Int>
// Line ~180: Get nearest key for point
fun getNearestKeyToken(x: Float, y: Float): Int
NeuralPredictionEngine.kt
// Line ~80: Run inference
suspend fun predict(tokens: IntArray): FloatArray
// Line ~150: Load ONNX model
fun loadModel(context: Context, language: String)
Typical inference times:
| Device Tier | Inference Time |
|---|
| High-end | 15-25 ms |
| Mid-range | 30-50 ms |
| Low-end | 80-150 ms |
