Gesture typing is a method of typing words on a touch-based keyboard by
creating a continuous trace passing through the relevant keys. This work is
aimed at developing a keyboard that supports gesture typing in Indic languages.
We begin by noting that when dealing with Indic languages, one needs to cater
to two different sets of users: (i) users who prefer to type in the native
Indic script (Devanagari, Bengali, etc.) and (ii) users who prefer to type in
the English script but want the output transliterated into the native script.
In both cases, we need a model that takes a trace as input and maps it to the
intended word. To enable the development of these models, we create and release
two datasets. First, we create a dataset containing keyboard traces for 193,658
words from 7 Indic languages. Second, we curate 104,412 English-Indic
transliteration pairs from Wikidata across these languages. Using these
datasets we build a model that performs path decoding, transliteration, and
transliteration correction. Unlike prior approaches, our proposed model does
not make co-character independence assumptions during decoding. The overall
accuracy of our model across the 7 languages varies from 70-95%.

本研究旨在开发一种支持印度语言手势输入的键盘，通过创建包含键盘轨迹的数据集来训练模型，并使用路径解码、音译和音译修正等技术对输入的轨迹进行映射以实现高达 70% 到 95% 的准确率。