Stringboard provides a stroke‑and component‑based Chinese text input engine for mobile devices, allowing users to enter characters by selecting individual strokes or radicals on a dual‑row keyboard. Its big‑data‑driven predictive algorithm ranks character and phrase suggestions in real time across Traditional, Simplified and Cantonese, with error‑tolerant parsing and offline support.
Funding
Funding not disclosed
Founders
Product
Problem
Chinese text entry relies on pinyin transcription or intricate key‑mapping systems (e.g., Cangjie), which impose a steep learning curve, limited dialect coverage, and high error rates for users unfamiliar with phonetic input or complex layouts.
Solution
Stringboard delivers a stroke‑and component‑based input engine that mirrors the natural act of writing Chinese characters. Users press large, ergonomically spaced keys to input individual strokes or radicals, optionally combining them to form full characters. A big‑data‑driven suggestion algorithm ranks the most probable characters and word completions in real time, supporting Traditional, Simplified, and Cantonese vocabularies without requiring pinyin. The patented technology provides high‑precision recognition with built‑in tolerance for input errors, enabling fast, accurate typing across all Chinese dialects on mobile platforms.
Target Audience
Primary users are native Chinese speakers, language learners, and professionals who require fast, accurate typing across Traditional, Simplified, and Cantonese scripts, as well as enterprises deploying Chinese text entry solutions in education or productivity software.
Features
- Dual‑row keyboard layout: bottom row for stroke entry, top row for component (radical) selection, allowing mixed stroke/component input.
- Large, high‑contrast keys that reduce mistyping and improve ergonomics on touchscreens.
- Big‑data powered predictive engine that ranks candidate characters and phrases based on usage frequency and context.
- Seamless toggle between Traditional, Simplified, and Cantonese suggestion sets, with dialect‑specific vocabularies.
- Error‑tolerant parsing that corrects out‑of‑order strokes and incomplete inputs, maintaining high recognition accuracy.
- Patented stroke‑component mapping algorithm optimized for low‑latency processing on iOS and Android devices.
- Free mobile app distribution with optional enterprise licensing for custom dictionaries and integration hooks.
- Offline mode that caches the prediction model for use without network connectivity.