A Smart Sliding Chinese Pinyin Input Method Editor for Touchscreen Devices
Zhen Meng, Hai Zhao · 2018
This paper presents a smart sliding Chinese pinyin Input Method Editor (IME) for touchscreen devices which allows user finger sliding from one key to another on the touchscreen instead of tapping keys one by one, while the target Chinese character sequence will be predicted during the sliding process to help the user entering Chinese sequences. Moreover, the layout of the virtual keyboard of our IME adapts to user sliding for more efficient inputting. The layout adaption process is utilized with Recurrent Neural Networks (RNN) and deep reinforcement learning and the pinyin-to-character converter is implemented with a sequence-to-sequence (Seq2Seq) model to predict the target Chinese sequence. A sliding simulator is built to automatically produce sliding samples for model training and virtual keyboard test. The key advantage of our IME is that nearly all its built-in tactics can be optimized automatically with deep learning algorithms on user behavior data, and the empirical studies verifies the effectiveness of the proposed model.