Improving mandarin predictive text input by augmenting pinyin initials with speech and tonal information

Abstract

Recently, a new technology called Haptic Voice Recognition (HVR) was proposed to enhance the speech recognition efficiency and accuracy for modern mobile devices, which has been successfully applied for robust English voice recognition. As both Pinyin and handwriting input methods work quite slow in mobile devices because of typing errors and ambiguity, it is interesting to apply this technology to assist Mandarin predictive text input. However, it is not straight- forward because the characteristics of Mandarin significantly differ from alphabetic western languages. In this paper, we investigated what possible haptic inputs are important and how these information can be incorporated to improve Mandarin text input. Various experiments were conducted and results have shown that with the help of acoustic and tonal information, the ambiguity of Pinyin Initial based Mandarin predictive text input is largely reduced and an oracle character error rate of 3.8% for the top 4 candidates could be achieved, which is usually the number of word candidates displayed on mobile devices. Our Mandarin HVR system has also shown its robustness in noisy environments. Copyright 2012 ACM.