Efficient, User-Friendly Text Input Method for Mobile Devices
Small form factor devices, such as cell phones, pose a variety of text entry problems. This talk introduces a new, easy-to-use Chinese text input solution for mobile devices. This unique text entry method uses handwritten phonetic input rather than handwritten ideograms. With the phonetic method, the user is able to write any Chinese character, Traditional or Simplified, using finger movement on a capacitive touch-sensitive surface that is mounted under a standard cell phone keymat. This talk also describes the Machine Learning techniques used to build the character recognition engines for the Chinese and English alphabets.
Dr. Nada Matic received her B.S. degree in Electrical Engineering from the University of Belgrade, and an M.S. and Ph.D. in Electrical Engineering from the City University of New York. She is currently Principal Research Scientist at Synaptics where she is heads the Pattern Recognition Group and the Usability Research. Prior to joining Synaptics she was with the Adaptive Systems Research Department at AT&T Bell Laboratories in Holmdel. Prior to that, she worked as a researcher in the Robotics Group, Mihailo Pupin Institute of Belgrade. Her main research focus is in Machine Learning, Pattern Recognition, Handwriting Recognition, text input methods, user interfaces for small computing and communication devices, and Human Computer Interactions.