Samsung Electronics Co., Ltd.

Ishan Vaid

Barath Raj Kandur Raja

Vibhav Agarwal

Ankur Agarwal

Mritunjai Chandra

Bharath C

Harshavardhana

Kranti Chalamalasetti

Methods and systems for predicting keystrokes using a neural network analyzing cumulative effects of a plurality of factors impacting the typing behavior of a user. The factors may include typing pattern, previous keystrokes, specifics of keyboard used for typing, and contextual parameters pertaining to a device displaying the keyboard and the user. A plurality of features may be extracted and fused to obtain a plurality of feature vectors. The plurality of feature vectors can be optimized and processed by the neural network to identify known features and learn unknown features that are impacting the typing behavior. Thereby, the neural network predicts keystrokes using the known and unknown features.

Methods and systems for predicting keystrokes using a unified neural network

Growing community of inventors

Bengaluru, India

Ishan Vaid