This paper presents an Automatic Reading Tutoring (ART) system using state-of-the-art speech recognition technologies aimed to improve children's oral reading ability. The features of this system include a compact and robust language model designed for detecting disfluencies in children's speech, low-footprint implementation, and built-in microphone array. Our system is targeting on hand-held devices to provide better accessibility, flexibility, and freedom for children's reading practice. The focus of this paper is on the current system's architecture, which has achieved real-time performance on two hand-held, small-form-factor devices (UMPC and Motion Tablet), with the same detection rate and false alarm rate as on desktop PCs. We also report the latest effort on a prototype system running on a PDA (Windows Mobile 6).
Cite as: Li, X., Deng, L., Ju, Y.-C., Acero, A. (2008) Automatic children's reading tutor on hand-held devices. Proc. Interspeech 2008, 1733-1736, doi: 10.21437/Interspeech.2008-467
@inproceedings{li08g_interspeech,
author={Xiaolong Li and Li Deng and Yun-Cheng Ju and Alex Acero},
title={{Automatic children's reading tutor on hand-held devices}},
year=2008,
booktitle={Proc. Interspeech 2008},
pages={1733--1736},
doi={10.21437/Interspeech.2008-467}
}