BWB — Voice Ordering System

BWB features a sophisticated voice ordering system that uses on-device speech recognition and semantic NLU to process natural language coffee orders. The system runs entirely on-device for privacy and speed. **How it works:** - Converts menu items to 300-dimensional vectors using Apple's NLEmbedding - Stores embeddings in VectorIndex for fast similarity search - Hybrid search: 60% semantic similarity + 40% fuzzy text matching **Key features:** | Feature | Description | |---------|-------------| | On-device | No external API calls | | Alias support | "americano" matches "Iced Americano" | | Abbreviations | "latte" finds all latte variants | | Typo tolerance | Fuzzy matching with Levenshtein distance | **Performance:** - Embedding initialization: ~500ms (once at startup) - Semantic search: <50ms (SIMD optimized) - Returns top-5 matches with confidence scores | Slot | Values | Example | |------|--------|---------| | size | small, medium, large, xl | "large" → size: large (0.98) | | temperature | hot, iced, blended | "iced" → temp: iced (0.97) | | milk | whole, skim, oat, almond, soy, coconut | "with oat milk" → milk: oat (0.95) | | caffeine | regular, decaf, half-caf | "decaf" → caffeine: decaf (0.92) | | shots | 1-6 | "extra shot" → shots: 2 (0.90) | | syrup | vanilla, caramel, hazelnut, etc. | "vanilla" → syrup: vanilla (0.88) | | quantity | 1-10 | "two lattes" → quantity: 2 (0.95) |