This K-12 digital event ticketing app has peaked in the Top 5 in the App Store for the Sports category. I was the lead developer on the iOS side and worked on Android for a few tasks.

Technology implemented include:

• Swift for both UIKit and SwiftUI
• Core Bluetooth for Bluetooth LE beacons (iBeacons)
• Core ML for a custom part-of-speech tagger model to support natural language search
• Secure authentication with Clerk
• Google Firebase / Crashlytics
• XCTest for unit testing
• Xcode Cloud with GitHub for CI/CD

This is an effort to explore a combination of technologies under the umbrella of artificial intelligence to create a tool for translating the Navajo (Diné) language into American English.

The project’s natural language processing aspect focuses on Apple’s Core ML word tagger model (a parts-of-speech tagger variant) to assist with interlinear translation. The training data come from custom spreadsheets built with over 12000 (and growing) word-tokenized records containing words, phrases, and long textual passages, totaling more than 54000 tokens. Once the dataset considerably grows, this project will likely follow the interlinear tagging with a second-phase custom polysynthetic tokenizer (for deep verb analysis) and a transformer model for true translation.

The Swift Package for the framework in on GitLab at https://www.twine.net/signin The “Navajo to English Translator” is in the App Store.